649 citations as recorded by crossref.

1. Evaluation of MAIAC aerosol retrievals over China Z. Zhang et al.
2. Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China N. Liu et al.
3. Assessing discrepancies in global aerosol trends from satellites, models and reanalyses R. Urraca et al.
4. A Sequence-to-Sequence Transformer Model for Satellite Retrieval of Aerosol Optical and Microphysical Parameters from Space L. Zhang et al.
5. Climatological Characteristics and Aerosol Loading Trends from 2001 to 2020 Based on MODIS MAIAC Data for Tianjin, North China Plain Z. Wu et al.
6. High-Resolution Mapping of Aerosol Optical Depth and Ground Aerosol Coefficients for Mainland China L. Li
7. Effects of COVID-19 lockdowns on fine particulate matter concentrations M. Hammer et al.
8. Long-term validation and error analysis of DB and MAIAC aerosol products over bright surface of China W. Ji et al.
9. The relationship between directional area scattering factor and foliage clumping based on DSCOVR EPIC data over Australian TERN sites J. Pisek et al.
10. A new generation aerosol optical depth dataset based on AVHRR data over China from 1981 to 2000 Y. Che et al.
11. Satellite-based aerosol optical depth estimates over the continental U.S. during the 2020 wildfire season: Roles of smoke and land cover J. Daniels et al.
12. Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter D. Zhang et al.
13. Remote sensing estimation of surface PM2.5 concentrations using a deep learning model improved by data augmentation and a particle size constraint S. Yin et al.
14. Two decades of high-resolution aerosol product over the Sierra Nevada Mountain region (SE Spain): Spatio-temporal distribution and impact on ecosystems A. del Águila et al.
15. From lowland plains to the Altiplano: The impacts of regional transport of wildfire smoke on the air quality of Bolivian cities E. Mollinedo et al.
16. Remote sensing of air pollutants in China to study the effects of emission reduction policies on air quality G. de Leeuw et al.
17. 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.
18. An improved meteorological variables-based aerosol optical depth estimation method by combining a physical mechanism model with a two-stage model F. Li et al.
19. A Generalized Aerosol Algorithm for Multi‐Spectral Satellite Measurement With Physics‐Informed Deep Learning Method J. Jiang et al.
20. Assessment of the vertical distribution of speciated aerosol absorption over South Asia using spaceborne LIDAR and ground-based observations N. Lakshmi et al.
21. Improving the Estimation of PM2.5 Concentration in the North China Area by Introducing an Attention Mechanism into Random Forest L. Zhang et al.
22. Comparison of different methods of determining land surface reflectance for AOD retrieval Q. Wang et al.
23. Influence of Spatial Resolution on Satellite-Based PM2.5 Estimation: Implications for Health Assessment H. Bai et al.
24. 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.
25. Linking land development to ecological and atmospheric change: remote sensing insights from Egypt’s new delta A. El-Zeiny et al.
26. Short-term effects of exposure to ambient PM1, PM2.5, and PM10 on ischemic and hemorrhagic stroke incidence in Shandong Province, China H. Wu et al.
27. Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees J. Wei et al.
28. On the retrieval of aerosol optical depth over cryosphere using passive remote sensing L. Mei et al.
29. Spatiotemporal imputation of MAIAC AOD using deep learning with downscaling L. Li et al.
30. Performance assessment and application of AlphaEarth embedding in air quality - Changchun PM2.5 Case C. Fang et al.
31. Validation and Comparison of Long-Term Accuracy and Stability of Global Reanalysis and Satellite Retrieval AOD X. Su et al.
32. 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.
33. Shapley values reveal the drivers of soil organic carbon stock prediction A. Wadoux et al.
34. Quantifying uncertainty for remote spectroscopy of surface composition D. Thompson et al.
35. 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.
36. Satellite-Derived 1-km-Resolution PM1 Concentrations from 2014 to 2018 across China J. Wei et al.
37. Deterioration of air quality associated with the 2020 US wildfires M. Filonchyk et al.
38. Gap-filling MODIS daily aerosol optical depth products by developing a spatiotemporal fitting algorithm T. Zhang et al.
39. Assessment of fine particle variability and sources in Nairobi, Kenya with WRF-CHIMERE simulations, surface measurements, and satellite observations E. Nyaga et al.
40. 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.
41. Harmonized Landsat and Sentinel-2 Data with Google Earth Engine E. Berra et al.
42. Effects of Fire Plume Height on the Geophysical Estimation of Surface Fine Particulate Matter from Satellite Aerosol Optical Depth during North American Wildfires I. Singh et al.
43. Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions L. Liang et al.
44. Ensemble averaging based assessment of spatiotemporal variations in ambient PM2.5 concentrations over Delhi, India, during 2010–2016 S. Mandal et al.
45. The Relationship Between MAIAC Smoke Plume Heights and Surface PM M. Cheeseman et al.
46. Estimating 1-km-resolution PM2.5 concentrations across China using the space-time random forest approach J. Wei et al.
47. Inferring iron-oxide species content in atmospheric mineral dust from DSCOVR EPIC observations S. Go et al.
48. Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm A. Sinyuk et al.
49. Identification of Aerosol Pollution Hotspots in Jiangsu Province of China Y. Wang et al.
50. Accuracy assessment and climatology of MODIS aerosol optical properties over North Africa A. Merdji et al.
51. Retrieval of aerosol optical depth from INSAT-3DR for accurate geostationary monitoring of regional and temporal aerosol dynamics C. Tandule et al.
52. Enhancing Estimation of Fine Particulate Matter Chemical Composition across North America by Including Geophysical A Priori Information in Deep Learning with Uncertainty Quantification S. Shen et al.
53. Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire X. Ye et al.
54. A Deep-Neural-Network-Based Aerosol Optical Depth (AOD) Retrieval from Landsat-8 Top of Atmosphere Data L. She et al.
55. Robust Analysis of PM2.5 Concentration Measurements in the Ecuadorian Park La Carolina W. Hernandez et al.
56. Impact of COVID-19 induced lockdown on land surface temperature, aerosol, and urban heat in Europe and North America B. Parida et al.
57. An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation N. Schutgens et al.
58. A deep learning-based imputation method for missing gaps in satellite aerosol products by fusing numerical model data N. Liu et al.
59. First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI S. Li et al.
60. Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States “Gigafire” P. Makkaroon et al.
61. Accuracy assessment of MODIS land aerosol optical thickness algorithms using AERONET measurements over North America H. Jethva et al.
62. Evaluation of urban PM2.5 concentrations over 73 major cities and their association with satellite Aerosol Optical Depth: A global analysis of ambient air pollution D. Stratoulias et al.
63. Urban PM2.5 concentration monitoring: A review of recent advances in ground-based, satellite, model, and machine learning integration S. Lolli
64. 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.
65. Review: Strategies for using satellite-based products in modeling PM2.5 and short-term pollution episodes M. Sorek-Hamer et al.
66. Surface and satellite observations of air pollution in India during COVID-19 lockdown: Implication to air quality Y. Sathe et al.
67. Effects of Air Pollutants on Summer Precipitation in Different Regions of Beijing Y. Yang et al.
68. Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI F. Yin et al.
69. Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S. X. Ye et al.
70. Comparative evaluation of backpropagation neural network and genetic algorithm-backpropagation neural network models for PM2.5 concentration prediction based on aerosol optical depth, meteorological factors, and air pollutants J. Gu et al.
71. Initial assessment Himawari-9 AHI aerosol optical depth over land H. Lin et al.
72. Evaluation and comparison of VIIRS dark target and deep blue aerosol products over land Q. Wang et al.
73. Using deep ensemble forest for high-resolution mapping of PM2.5 from MODIS MAIAC AOD in Tehran, Iran H. Bagheri
74. Spatial downscaling of surface ozone concentration calculation from remotely sensed data based on mutual information X. Wang et al.
75. A Hybrid Approach to Estimate Spatially and Temporally Resolved Pm2.5 Distributions from Multi-Sourced Aod Data Q. Pu & Y. Eun-Hye
76. Benefits of High Resolution PM2.5 Prediction using Satellite MAIAC AOD and Land Use Regression for Exposure Assessment: California Examples H. Lee
77. Accuracy assessment on eight public PM2.5 concentration datasets across China Y. Di et al.
78. Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998–2018) M. Hammer et al.
79. A physical knowledge-based machine learning method for near-real-time dust aerosol properties retrieval from the Himawari-8 satellite data J. Li et al.
80. Assessment of methods for mapping snow albedo from MODIS R. Palomaki et al.
81. Towards improved retrieval of aerosol properties from the geostationary orbit with the new Meteosat Third Generation-Imager satellite A. Georgeot et al.
82. A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al.
83. Big data analyses for determining the spatio-temporal trends of air pollution due to wildfires in California using Google Earth Engine A. Saim & M. Aly
84. Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season Z. Lu et al.
85. Influence of transboundary air pollution into the atmosphere of Kathmandu Valley H. Kafle et al.
86. Radiative interaction of atmosphere and surface: Write-up with elements of code S. Korkin & A. Lyapustin
87. Development and Evaluation of Spatio-Temporal Air Pollution Exposure Models and Their Combinations in the Greater London Area, UK K. Dimakopoulou et al.
88. Mineral dust optical properties for remote sensing and global modeling: A review P. Castellanos et al.
89. AERONET Remotely Sensed Measurements and Retrievals of Biomass Burning Aerosol Optical Properties During the 2015 Indonesian Burning Season T. Eck et al.
90. A Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5 L. Li
91. Long short-term memory network model to estimate PM2.5 concentrations with missing-filled satellite data in Beijing S. Jia et al.
92. Global aerosol retrieval over land from Landsat imagery integrating Transformer and Google Earth Engine J. Wei et al.
93. Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data X. Ceamanos et al.
94. Continuity between NASA MODIS Collection 6.1 and VIIRS Collection 2 land products M. Román et al.
95. Matrix exponential in C/C++ version of vector radiative transfer code IPOL S. Korkin & A. Lyapustin
96. Himawari-8/AHI Aerosol Optical Depth Detection Based on Machine Learning Algorithm Y. Chen et al.
97. Spatio-temporal variations of aerosol optical depth over Ukraine under the Russia-Ukraine war D. Jiadan et al.
98. Conversion from Ross-Li to Rahman-Pinty-Verstraete Model Parameterizations of Surface Bidirectional Reflectance T. Huang et al.
99. The Impact of the Control Measures during the COVID-19 Outbreak on Air Pollution in China C. Fan et al.
100. Retrievals of Aerosol Optical Depth and Spectral Absorption From DSCOVR EPIC A. Lyapustin et al.
101. Analysis of a severe dust storm and its impact on air quality conditions using WRF-Chem modeling, satellite imagery, and ground observations F. Karagulian et al.
102. The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 A. Sinyuk et al.
103. Merging regional and global aerosol optical depth records from major available satellite products L. Sogacheva et al.
104. A Erosol S  Characteristics, Sources, and Drive Factors Analysis  In Typical Megacities, Nw China z. zhang
105. Machine learning-driven regional prediction of PM2.5 concentrations in the eastern mediterranean bridging spatial data gaps in air quality monitoring İ. Gürtepe et al.
106. Meteorological controls on daily variations of nighttime surface urban heat islands J. Lai et al.
107. Assessing uncertainties of a geophysical approach to estimate surface fine particulate matter distributions from satellite-observed aerosol optical depth X. Jin et al.
108. Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China X. Chen et al.
109. Recurring South Asian smog episodes: Call for regional cooperation and improved monitoring M. Khokhar et al.
110. Multi-Criteria Assessment for City-Wide Rooftop Solar PV Deployment: A Case Study of Bandung, Indonesia A. Sakti et al.
111. Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al.
112. Multi-Decadal Trends in Aerosol Optical Depth of the Main Aerosol Species Based on MERRA-2 Reanalysis: A Case Study in the Baltic Sea Basin E. Mancinelli et al.
113. Climatology and variability of smoke aerosols from MAIAC EPIC observations over North America (2016–2024) M. Choi et al.
114. 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.
115. Impact of satellite AOD data on top-down estimation of biomass burning particulate matter emission X. Ye et al.
116. City-Scale Aerosol Loading Changes in the Sichuan Basin from 2001 to 2020 as Revealed by MODIS 1 km Aerosol Product R. Wang & H. Cai
117. A new constant scattering angle solar geometry definition for normalization of GOES-R ABI reflectance times series to support land surface phenology studies S. Gao et al.
118. Evaluating machine learning methods for PM2.5 estimation using satellite AOD, low-cost and reference-grade monitors in Kampala P. Adong et al.
119. Limitations of cloud cover for optical remote sensing of agricultural areas across South America V. Prudente et al.
120. Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al.
121. Spatiotemporally continuous estimates of daily 1-km PM2.5 concentrations and their long-term exposure in China from 2000 to 2020 Q. He et al.
122. Estimation of PM2.5 Concentration across China Based on Multi-Source Remote Sensing Data and Machine Learning Methods Y. Yang et al.
123. Spatiotemporal PM2.5 variations and its response to the industrial structure from 2000 to 2018 in the Beijing-Tianjin-Hebei region W. Xue et al.
124. Study on Spatial Changes in PM2.5 before and after the COVID-19 Pandemic in Southwest China X. Li et al.
125. The incidence and magnitude of the hot-spot bidirectional reflectance distribution function (BRDF) signature in GOES-16 Advanced Baseline Imager (ABI) 10 and 15 minute reflectance over north America Z. Li et al.
126. Sub-continental-scale carbon stocks of individual trees in African drylands C. Tucker et al.
127. Intercomparison of Aerosol Types Reported as Part of Aerosol Product Retrieval over Diverse Geographic Regions S. Falah et al.
128. Air Quality over China G. de Leeuw et al.
129. Preliminary Retrieval and Validation of Aerosol Optical Depths from FY-4B Advanced Geostationary Radiation Imager Images D. Zhou et al.
130. Generation and Evaluation of LAI and FPAR Products from Himawari-8 Advanced Himawari Imager (AHI) Data Y. Chen et al.
131. A practical guide to writing a radiative transfer code S. Korkin et al.
132. Gaussian Markov random fields improve ensemble predictions of daily 1 km PM2.5 and PM10 across France I. Hough et al.
133. Estimating PM2.5 Concentrations Using the Machine Learning RF-XGBoost Model in Guanzhong Urban Agglomeration, China L. Lin et al.
134. Influence of Spatial Resolution and Retrieval Frequency on Applicability of Satellite-Predicted PM2.5 in Northern China R. Li et al.
135. A State of the Science Review of Wildfire-Specific Fine Particulate Matter Data Sources, Methods, and Models A. Orr et al.
136. Spatio-temporal air quality assessment in Tehran, Iran, during the COVID-19 lockdown periods M. Bagherinia et al.
137. Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume M. Majdzadeh et al.
138. Estimating PM2.5 in Southern California using satellite data: factors that affect model performance J. Stowell et al.
139. A comprehensive review delineates advancements in retrieving particulate matter utilising satellite aerosol optical depth: Parameter consideration, data processing, models development and future perspectives S. Padimala & C. Matli
140. A Multi-Wavelength Deep Neural Network Framework for Synergistic Retrieval of AOD, FMF, and AAOD from TROPOMI B. Xu et al.
141. Geographical and temporal encoding for improving the estimation of PM2.5 concentrations in China using end-to-end gradient boosting N. Yang et al.
142. Characterization of dust activation and their prevailing transport over East Asia based on multi-satellite observations M. Tao et al.
143. Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning R. Stirnberg et al.
144. Twenty Years of High Spatiotemporal Resolution Estimates of Daily PM2.5 in West Africa Using Satellite Data, Surface Monitors, and Machine Learning D. Westervelt et al.
145. How Important Is Satellite-Retrieved Aerosol Optical Depth in Deriving Surface PM2.5 Using Machine Learning? Z. Tian et al.
146. Towards a New MAX-DOAS Measurement Site in the Po Valley: Aerosol Optical Depth and NO2 Tropospheric VCDs E. Castelli et al.
147. Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring C. Chen et al.
148. Advanced Time series Multi-wavelength AOD Transformer (TMAT) model: joint retrieval of aerosol optical and microphysical properties using Himawari-8 AHI data L. She et al.
149. Satellite-Based Optimization and Planning of Urban Ventilation Corridors for a Healthy Microclimate Environment D. Gong et al.
150. Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas H. Lin et al.
151. Environmental hazards posed by mine dust, and monitoring method of mine dust pollution using remote sensing technologies: An overview H. Yu & I. Zahidi
152. Clustering time series analysis of tropospheric NO2 and AOD satellite data in global megacities: exploring patterns linked to energy-related variables M. Volke & L. González-Rodríguez
153. Columnar and surface urban aerosol in the Moscow megacity according to measurements and simulations with the COSMO-ART model N. Chubarova et al.
154. Accuracy and error cause analysis, and recommendations for usage of Himawari-8 aerosol products over Asia and Oceania L. Feng et al.
155. Assessment of the impact of waste fires on air quality and atmospheric aerosol optical depth: A case study in Poland R. Oleniacz et al.
156. An accurate and efficient forecast framework for fine PM2.5 maps using spatiotemporal recurrent neural networks N. Liu et al.
157. North American Fine Particulate Matter Chemical Composition for 2000–2022 from Satellites, Models, and Monitors: The Changing Contribution of Wildfires A. van Donkelaar et al.
158. Mesoscale Impacts on Cold Season PM<sub>2.5</sub> in the Yukon Flats S. Edwin & N. Mölders
159. Evaluation and Comparison of Spatio-Temporal Relationship between Multiple Satellite Aerosol Optical Depth (AOD) and Near-Surface PM2.5 Concentration over China Q. Xu et al.
160. A Novel Atmospheric Correction Algorithm to Exploit the Diurnal Variability in Hypertemporal Geostationary Observations W. Wang et al.
161. Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth H. Zhu et al.
162. Heat flux assumptions contribute to overestimation of wildfire smoke injection into the free troposphere L. Thapa et al.
163. Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning Q. Xie & Q. Sun
164. First Retrieval of AOD at Fine Resolution Over Shallow and Turbid Coastal Waters From MODIS Y. Wang et al.
165. Improvement of spatial-temporal resolution of aerosol profile by using multi-source satellite data over the Persian Gulf M. Pashayi et al.
166. Using PlanetScope NDVI time series to detect the phenology of individual trees in the Sahel Y. Fitts et al.
167. Quantifying urban heat island and pollutant nexus: A novel geospatial approach K. Arunab & A. Mathew
168. Data-driven estimates of evapotranspiration and its controls in the Congo Basin M. Burnett et al.
169. Maternal Exposure to PM 2.5 and the Risk of Congenital Heart Defects in 1.4 Million Births: A Nationwide Surveillance-Based Study X. Yuan et al.
170. Vertical distribution of smoke aerosols over upper Indo-Gangetic Plain K. Vinjamuri et al.
171. Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives Y. Zhang et al.
172. Aerosol optical depth in the Yellow River Basin during 2000-2023: Spatiotemporal variations and potential impacting factors R. Zhu et al.
173. Improved Land AOD Retrieval of GK-2A/AMI via Background Surface Reflectance Based on sRTLS-BRDF Inversion D. Jung et al.
174. Long-Term Exposure to Fine Particulate Matter and Cardiovascular Disease in China F. Liang et al.
175. LGHAP v2: a global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big Earth data analytics K. Bai et al.
176. Evaluation of Novel NASA Moderate Resolution Imaging Spectroradiometer and Visible Infrared Imaging Radiometer Suite Aerosol Products and Assessment of Smoke Height Boundary Layer Ratio During Extreme Smoke Events in the Western USA S. Loría‐Salazar et al.
177. A high-precision aerosol retrieval algorithm for FY-3D MERSI-II images Q. Wang et al.
178. Predicting Fine Particulate Matter (PM2.5) in the Greater London Area: An Ensemble Approach using Machine Learning Methods M. Danesh Yazdi et al.
179. An integrated atmospheric-topographic correction framework for land surface reflectance estimation using a spatial-spectral Attention U-Net model Y. Ma et al.
180. Land surface temperature and transboundary air pollution: a case of Bangkok Metropolitan Region T. Sarker et al.
181. Solar energy resource availability under extreme and historical wildfire smoke conditions K. Corwin et al.
182. Algorithm for the Reconstruction of the Ground Surface Reflectance in the Visible and Near IR Ranges from MODIS Satellite Data with Allowance for the Influence of Ground Surface Inhomogeneity on the Adjacency Effect and of Multiple Radiation Reflection M. Tarasenkov et al.
183. First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation J. Dong et al.
184. Long-term satellite-based estimates of air quality and premature mortality in Equatorial Asia through deep neural networks N. Bruni Zani et al.
185. Effect of lockdown due to COVID-19 on environmental pollutant: a comparative study between top three countries of the world S. Kumar
186. Influence of trees on landscape temperature in semi-arid agro-ecosystems of East Africa L. Villani et al.
187. Downwind Ozone Changes of the 2019 Williams Flats Wildfire: Insights From WRF‐Chem/DART Assimilation of OMI NO2, HCHO, and MODIS AOD Retrievals A. Pouyaei et al.
188. Retrieving aerosol single scattering albedo from FY-3D observations combining machine learning with radiative transfer model Q. Wang et al.
189. Temporal and spatial distribution mapping of particulate matter in southwest of Iran using remote sensing, GIS, and statistical techniques A. Soleimany et al.
190. Study on the Lagged Response Mechanism of Vegetation Productivity Under Atypical Anthropogenic Disturbances Based on XGBoost-SHAP J. Sun et al.
191. XIS-PM2.5: A daily spatiotemporal machine-learning model for PM2.5 in the contiguous United States A. Just et al.
192. Characterizing aerosols during forest fires over Uttarakhand region in India using multi-satellite remote sensing data S. Verma et al.
193. Daily 1 km terrain resolving maps of surface fine particulate matter for the western United States 2003–2021 A. Swanson et al.
194. Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations L. She et al.
195. Evaluation and improvement of MODIS aerosol optical depth products over China Y. Li et al.
196. Measuring and Monitoring Urban Impacts on Climate Change from Space C. Milesi & G. Churkina
197. The comparison of AOD-based and non-AOD prediction models for daily PM2.5 estimation in Guangdong province, China with poor AOD coverage G. Chen et al.
198. Evaluation and comparison of MODIS aerosol optical depth retrieval algorithms over Brazil A. Rudke et al.
199. A Bayesian PM2.5 model incorporating planetary boundary layer height variability in Tabriz, Iran A. Shikhesmailie et al.
200. Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China Z. Sun et al.
201. Bayesian Geostatistics Using Predictive Stacking L. Zhang et al.
202. Multiparameter Aerosol Simultaneous Retrieval Combining Satellite Remote Sensing and Atmospheric Simulation Using Space-Time Transformer (STTF) Model Y. Fan et al.
203. Association between exposure to PM2.5 and black carbon and the risk of childhood leukemia in Tehran: A case–control study with critical exposure time windows S. Norzaee et al.
204. Predicting annual PM2.5 in mainland China from 2014 to 2020 using multi temporal satellite product: An improved deep learning approach with spatial generalization ability Z. Wang et al.
205. Satellite Monitoring for Air Quality and Health T. Holloway et al.
206. Impact of aerosols on atmospheric processes and climate variability: A synthesis of recent research findings S. Perumpully & S. Gautam
207. LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion K. Bai et al.
208. The mismatch between PM2.5 exposure and related health burden during 2000–2023 in the Sichuan Basin, China H. Lu et al.
209. Estimation of fine spatial resolution all-sky surface net shortwave radiation over mountainous terrain from Landsat 8 and Sentinel-2 data Y. Ma et al.
210. Scene invariants for quantifying radiative transfer uncertainty D. Thompson et al.
211. Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data L. She et al.
212. Sensitivity of aerosol models in satellite-based AOD retrieval: a quantitative analysis using Oceansat-3/OCM-3 multi-spectral measurements A. Athul et al.
213. Spatio-Temporal Dynamics of Aerosol Optical Thickness derived Using MODIS-MAIAC Algorithm at a High Spatial Resolution Along with the HYSPLIT Trajectory Model A. Chauhan et al.
214. Profiling of Dust and Urban Haze Mass Concentrations during the 2019 National Day Parade in Beijing by Polarization Raman Lidar Z. Wang et al.
215. Influence of Vegetation Phenology on the Temporal Effect of Crop Fractional Vegetation Cover Derived from Moderate-Resolution Imaging Spectroradiometer Nadir Bidirectional Reflectance Distribution Function–Adjusted Reflectance Y. Lin et al.
216. Estimation of Daily Seamless PM2.5 Concentrations with Climate Feature in Hubei Province, China W. Ni et al.
217. Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments Z. Chen et al.
218. Uncertainty in Aqua-MODIS Aerosol Retrieval Algorithms During COVID-19 Lockdown M. Bilal et al.
219. Augmenting Satellite Remote Sensing with AERONET-OC for Plume Monitoring in the Chesapeake Bay S. Smith et al.
220. Comprehensive Validation of MODIS-MAIAC Aerosol Products and Long-Term Aerosol Detection over an Urban–Rural Area Around Rome in Central Italy V. Terenzi et al.
221. Assessing air pollutant emissions from undercity mines using different satallite tropospheric monitoring sensor data H. Akcin et al.
222. Consistency of Aerosol Optical Properties between MODIS Satellite Retrievals and AERONET over a 14-Year Period in Central–East Europe L. Deaconu et al.
223. Surface Reflectance and Aerosol Retrieval from SPOT-VGT and PROBA-V in the Mission Exploitation Platform Environment M. Luffarelli et al.
224. A novel mechanism-guided retrieval framework for mangrove chlorophyll content considering leaf area index and spectral resolution based on active learning hybrid model B. Fu et al.
225. Predicting gestational personal exposure to PM2.5 from satellite-driven ambient concentrations in Shanghai Q. Zhu et al.
226. Estimating the Impact of COVID-19 on the PM2.5 Levels in China with a Satellite-Driven Machine Learning Model Q. Li et al.
227. Parameterization of size of organic and secondary inorganic aerosol for efficient representation of global aerosol optical properties H. Zhu et al.
228. 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
229. Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM2.5) using satellite data over large regions A. Just et al.
230. Optimal spatio-temporal interpolation of aerosol optical depth over China using fixed rank kriging Y. Kong et al.
231. Optimizing GAIN model to improve AOD imputation using MODIS MAIAC data and multi-source data fusion as an example A. Malarvizhi et al.
232. First high temporal resolution retrievals of AOD over shallow and turbid coastal waters for Himawari-8 Y. Wang et al.
233. An Optimization Approach for Estimating Multiple Land Surface and Atmospheric Variables From the Geostationary Advanced Himawari Imager Top-of-Atmosphere Observations H. Ma et al.
234. Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images R. Paulino et al.
235. Optimizing afforestation and reforestation strategies to enhance ecosystem services in critically degraded regions . Fahrudin et al.
236. First validation of Earth Reflector Type Index (p) parameter from DSCOVR EPIC VESDR data product using Terrestrial Ecosystem Research Network observing sites in Australia J. Pisek et al.
237. Estimation of ambient PM2.5 in Iraq and Kuwait from 2001 to 2018 using machine learning and remote sensing J. Li et al.
238. Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations V. Martins et al.
239. AeroTrans: Hourly AOD retrieval over land from MSG-1/SEVIRI imagery integrating Transformer and transfer learning Y. Fan et al.
240. 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.
241. Reconstructing aerosol optical depth using spatiotemporal Long Short-Term Memory convolutional autoencoder L. Liang et al.
242. Operational Evaluation of a Wildfire Air Quality Model from a Forecaster Point of View B. Ainslie et al.
243. A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al.
244. Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition Y. Ding et al.
245. Analysis of the spatial and temporal distribution characteristics of AOD in typical industrial cities in northwest China and the influence of meteorological factors H. Meng et al.
246. Satellite-observed vegetation responses to aerosols variability Z. Zhang et al.
247. Satellite data to support air quality assessment and management T. Holloway et al.
248. Validation and Analysis of MAIAC AOD Aerosol Products in East Asia from 2011 to 2020 P. Wang et al.
249. Impacts of wildfire-season air quality on park and playground visitation in the Northwest United States K. Mullan et al.
250. Estimation and Evaluation of Land Surface Reflectance from a Next-Generation Geostationary Meteorological Satellite, Himawari-8/9 AHI W. LI et al.
251. Remote sensing tracks daily radial wood growth of evergreen needleleaf trees J. Eitel et al.
252. Geographic Graph Network for Robust Inversion of Particulate Matters L. Li
253. Assessment of the impact of discontinuity in satellite instruments and retrievals on global PM2.5 estimates M. Hammer et al.
254. Improved Himawari-8 10-minute scale aerosol optical depth product using deep neural network over Japan Y. Tan et al.
255. Aerosol characteristics at the three poles of the Earth as characterized by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations Y. Yang et al.
256. Quasi‐Global Maps of Daily Aerosol Optical Depth From a Ring of Five Geostationary Meteorological Satellites Using AERUS‐GEO X. Ceamanos et al.
257. A MAIA-like modeling framework to estimate PM2.5 mass and speciation concentrations with uncertainty Z. Jin et al.
258. Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data L. She et al.
259. Direct radiative effects of aerosols and clouds and their impacts on the ecosystem gross primary productivity in summer at typical sites in China X. Deng et al.
260. The spatiotemporal heterogeneity of the relationship between PM2.5 concentrations and the surface urban heat island effect in Beijing, China Z. Li et al.
261. 基于GF-5卫星遥感数据的大气CO2快速反演方法 孙. Sun Zhiqiang et al.
262. Satellite mapping of PM2.5 episodes in the wintertime San Joaquin Valley: a “static” model using column water vapor R. Chatfield et al.
263. Does improved tenure security reduce fires? Evidence from the Greece land registry L. Diao & H. Song
264. Efficient Multiangle Polarimetric Retrieval of Aerosols Using Data-Driven Deep Learning Method W. Man et al.
265. Analysis and Variation of the Maiac Aerosol Optical Depth in Underexplored Urbanized Area of National Capital Region, India V. Sharma et al.
266. An improved deep learning network for AOD retrieving from remote sensing imagery focusing on sub-pixel cloud H. Cai et al.
267. A two-stage algorithm to estimate ground-level PM2.5 concentration levels in Madrid (Spain) from AOD satellite data and surface proxies J. Cordero
268. New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS) F. Tuli et al.
269. A review of statistical methods used for developing large-scale and long-term PM2.5 models from satellite data Z. Ma et al.
270. Potential role of urban forest in removing PM2.5: A case study in Seoul by deep learning with satellite data A. Lee et al.
271. Development of an aerosol optical depth retrieval algorithm based on an improved scattering angle scheme for Advanced Himawari Imager observations J. Jin et al.
272. Effect of Scattering Angle on Earth Reflectance A. Marshak et al.
273. Relationship between respiratory diseases and environmental conditions: a time-series analysis in Eastern Amazon M. Moura et al.
274. The global spatial-temporal distribution and EOF analysis of AOD based on MODIS data during 2003–2021 X. Tian et al.
275. NO2 emissions from oil refineries in the Mississippi Delta M. Filonchyk & M. Peterson
276. Global hourly seamless AOD through measurement-adjusted machine learning fusion of multi-satellite and reanalysis data Y. Ding et al.
277. Characterization of temporal and spatial variability of aerosols from ground-based climatology: towards evaluation of satellite mission requirements C. Chen et al.
278. The ChinaHighPM10 dataset: generation, validation, and spatiotemporal variations from 2015 to 2019 across China J. Wei et al.
279. Effects of aerosol on terrestrial gross primary productivity in Central Asia W. Ma et al.
280. A Satellite-Based High-Resolution (1-km) Ambient PM2.5 Database for India over Two Decades (2000–2019): Applications for Air Quality Management S. Dey et al.
281. Environmental factors modulate the diffuse fertilization effect on gross primary productivity across Chinese ecosystems X. Gui et al.
282. Impacts of long-range transport of aerosols and biomass burning smoke from the Bay of Bengal to the Indian Ocean B. de Foy et al.
283. 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.
284. Performance and generalizability impacts of incorporating location encoders into deep learning for dynamic PM 2.5 estimation M. Karimzadeh et al.
285. Long-term exposure to PM 2.5 and all-cause mortality: 10-year follow-up of a multicentre population-based prospective study among rural Chinese population Y. Zhao et al.
286. Tracking ambient PM2.5 build-up in Delhi national capital region during the dry season over 15 years using a high-resolution (1 km) satellite aerosol dataset S. Chowdhury et al.
287. Spatiotemporal variation and provincial scale differences of the AOD across China during 2000–2021 G. de Leeuw et al.
288. Scaled RTLS BRDF model extended to high zenith angles A. Lyapustin et al.
289. Evaluation of modeled smoke plumes of wildfires in the Argentinian Patagonia, against satellite observations M. García Ferreyra et al.
290. Ambient PM2.5 Estimates and Variations during COVID-19 Pandemic in the Yangtze River Delta Using Machine Learning and Big Data D. Lu et al.
291. Optimizing meteorological predictions to improve photovoltaic power generation in coastal areas Y. Wu et al.
292. Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and central Africa M. Choi et al.
293. Estimating PM2.5 with high-resolution 1-km AOD data and an improved machine learning model over Shenzhen, China W. Chen et al.
294. All-Weather Precipitable Water Vapor Retrieval over Land Using Integrated Near-Infrared and Microwave Satellite Observations S. Song et al.
295. PM2.5 and PM10 during COVID-19 lockdown in Kuwait: Mixed effect of dust and meteorological covariates A. Al-Hemoud et al.
296. Type-based assessment of aerosol direct radiative effects: A proof-of-concept using GEOS-Chem and CATCH B. Sutherland & N. Meskhidze
297. Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach S. Mandal et al.
298. 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.
299. Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity A. Gumber et al.
300. High-resolution estimation of PM2.5 concentrations across China using multiple machine learning approaches and model fusion L. Meng et al.
301. Assessing socioeconomic and climate driven road maintenance priorities in Southeast Asia using remote sensing approach A. Sakti et al.
302. Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods M. Kim et al.
303. An Enhanced Aerosol Optical Depth Retrieval Algorithm for Particulate Observing Scanning Polarimeter (POSP) Data Over Land Z. Ji et al.
304. MODIS-Derived Arctic Melt Season Fog and Low Stratus over East Greenland Glaciers and the Ice Sheet H. Jiskoot et al.
305. Snow-corrected vegetation indices for improved gross primary productivity assessment in North American evergreen forests R. Wang et al.
306. Retrieval and Validation of AOD from Himawari-8 Data over Bohai Rim Region, China Q. Wang et al.
307. Calibration of the SNPP and NOAA 20 VIIRS sensors for continuity of the MODIS climate data records A. Lyapustin et al.
308. Evolution of aerosol optical depth over China in 2010–2024: increasing importance of meteorological influences C. Fan et al.
309. Impact of environmental attributes on the uncertainty in MAIAC/MODIS AOD retrievals: A comparative analysis S. Falah et al.
310. An intercomparison of SEMARA high-resolution AOD and MODIS operational AODs M. Bagherinia et al.
311. Quality Assessment and Application Scenario Analysis of AGRI Land Aerosol Product from the Geostationary Satellite Fengyun-4B in China N. Wang et al.
312. Long-term changes in aerosol loading over the ‘BIHAR’ State of India using nineteen years (2001–2019) of high-resolution satellite data (1 × 1 km2) M. Nair et al.
313. Spatiotemporal estimation of satellite-borne and ground-level NO2 using full residual deep networks L. Li & J. Wu
314. Spatial integration framework of solar, wind, and hydropower energy potential in Southeast Asia A. Sakti et al.
315. Synergistic data fusion of multimodal AOD and air quality data for near real-time full coverage air pollution assessment K. Li et al.
316. Absorbing Aerosol Optical Depth From OMI/TROPOMI Based on the GBRT Algorithm and AERONET Data in Asia D. Li et al.
317. Remote sensing of air pollution due to forest fires and dust storm over Balochistan (Pakistan) S. Tariq et al.
318. Unveiling Atmospheric Layers: Vertical Pollution Patterns and Prospects for High-Resolution Aerosol Retrievals Using the Eastern Mediterranean as a Case Study I. Rogozovsky et al.
319. Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US M. Childs et al.
320. Assessing PM2.5 concentrations in Tehran, Iran, from space using MAIAC, deep blue, and dark target AOD and machine learning algorithms S. Nabavi et al.
321. Exploring the Potential of DSCOVR EPIC Data to Retrieve Clumping Index in Australian Terrestrial Ecosystem Research Network Observing Sites J. Pisek et al.
322. Accounting for 3D radiative effects in MODIS aerosol retrievals near clouds using CALIPSO observations G. Wen et al.
323. Long-term MAX-DOAS measurements of NO2, HCHO, and aerosols and evaluation of corresponding satellite data products over Mohali in the Indo-Gangetic Plain V. Kumar et al.
324. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications J. Wei et al.
325. Atmospheric Correction of DSCOVR EPIC: Version 2 MAIAC Algorithm A. Lyapustin et al.
326. High aerosol loading over the Bohai Sea: Long-term trend, potential sources, and impacts on surrounding cities L. Li et al.
327. Evaluation and comparison of MODIS and MISR aerosol products with ground-based monitoring stations in the Amazon Basin V. Schumacher et al.
328. High-accuracy full-coverage PM 2.5 retrieval from 2014 to 2023 over China based on satellite remote sensing and hierarchical deep learning model Y. Fan et al.
329. Error characterization and analysis of aerosol products from the geostationary environment monitoring spectrometer (GEMS) G. Du et al.
330. Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part I: Conditions, approaches, performance and new possibilities P. Litvinov et al.
331. Fire Smoke Elevated the Carbonaceous PM2.5 Concentration and Mortality Burden in the Contiguous U.S. and Southern Canada Z. Jin et al.
332. Global evaluation and uncertainty analysis of MODIS Deep Blue and MAIAC aerosol products over bright surfaces P. Zhang et al.
333. Atmospheric pollutants in Rosario, Argentina analysed through remote sensing: Wildfires and COVID-19 lockdown effects M. Valle Seijo et al.
334. Grid-independent high-resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (12.5.0) J. Meng et al.
335. The delayed effect of wildfire season particulate matter on subsequent influenza season in a mountain west region of the USA E. Landguth et al.
336. A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading Y. Shi et al.
337. Calibration of Maxar Constellation Over Libya-4 Site Using MAIAC Technique M. Choi et al.
338. Satellite-Derived PM2.5 Composition and Its Differential Effect on Children’s Lung Function K. Chau et al.
339. An Ensemble Mean Method for Remote Sensing of Actual Evapotranspiration to Estimate Water Budget Response across a Restoration Landscape R. Petrakis et al.
340. MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm J. Limbacher et al.
341. Incorporating Low-Cost Sensor Measurements into High-Resolution PM2.5 Modeling at a Large Spatial Scale J. Bi et al.
342. Aerosol profiling using radiometric and polarimetric spectral measurements in the O2 near infrared bands: Estimation of information content and measurement uncertainties M. Choi et al.
343. Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia E. Kang et al.
344. Investigating the impact of drought and dust on oak trees decline in the West of Iran S. Sarab et al.
345. A decadal, hourly high-resolution satellite dataset of aerosol optical properties over East Asia J. Lee et al.
346. Integrating low-cost air quality sensor networks with fixed and satellite monitoring systems to study ground-level PM2.5 J. Li et al.
347. Performance of MODIS high-resolution MAIAC aerosol algorithm in China: Characterization and limitation M. Tao et al.
348. Performance evaluation for retrieving aerosol optical depth from the Directional Polarimetric Camera (DPC) based on the GRASP algorithm S. Jin et al.
349. Impact of environmental pollution on the retrieval of hourly aerosol products from Advanced Himawari Imager (AHI) over Beijing Q. Xu et al.
350. Space-Time Machine Learning Models to Analyze COVID-19 Pandemic Lockdown Effects on Aerosol Optical Depth over Europe S. Ibrahim et al.
351. Application of remote sensing data to assess environmental situation in Krasnoyarsk K. Krasnoshchekov et al.
352. Retrieval of UV–visible aerosol absorption using AERONET and OMI–MODIS synergy: spatial and temporal variability across major aerosol environments V. Kayetha et al.
353. Spatiotemporal Distributions of PM2.5 Concentrations in the Beijing–Tianjin–Hebei Region From 2013 to 2020 X. Yang et al.
354. Estimating High-Resolution PM2.5 Concentrations by Fusing Satellite AOD and Smartphone Photographs Using a Convolutional Neural Network and Ensemble Learning F. Wang et al.
355. Retrieval of Ground Surface Reflectance from MODIS Satellite Data with Allowance for Reflectance Heterogeneity and Rugged Topography M. Tarasenkov et al.
356. Aerosol characteristics from earth observation systems: A comprehensive investigation over South Asia (2000–2019) A. Mhawish et al.
357. Improvement of aerosol optical depth data for localized solar resource assessment C. Lin et al.
358. Satellite-based evidence of dust emission over Northern Canada I. Ashpole et al.
359. Monitoring of aerosol optical-microphysical properties from DPC/GF-5(02): A case study of dust event in north China plain Y. Cao et al.
360. Analyzing GOES-R ABI BRDF-adjusted EVI2 time series by comparing with VIIRS observations over the CONUS Y. Shen et al.
361. Climatology of aerosol component concentrations derived from multi-angular polarimetric POLDER-3 observations using GRASP algorithm L. Li et al.
362. Spatial validation reveals poor predictive performance of large-scale ecological mapping models P. Ploton et al.
363. Evaluation of Key Remote Sensing Features for Bushfire Analysis Z. Yang et al.
364. Estimation of monthly 1 km resolution PM2.5 concentrations using a random forest model over “2 + 26” cities, China J. Lu et al.
365. Revisiting dry season vegetation dynamics in the Amazon rainforest using different satellite vegetation datasets X. Xie et al.
366. On the Interplay between Desert Dust and Meteorology Based on WRF-Chem Simulations and Remote Sensing Observations in the Mediterranean Basin U. Rizza et al.
367. A robust and flexible satellite aerosol retrieval algorithm for multi-angle polarimetric measurements with physics-informed deep learning method M. Tao et al.
368. Detecting intra- and inter-annual variability in gross primary productivity of a North American grassland using MODIS MAIAC data R. Wang et al.
369. Aerosol optical depth climatology from the high-resolution MAIAC product over Europe: differences between major European cities and their surrounding environments L. Di Antonio et al.
370. A multi-analysis approach for estimating regional health impacts from the 2017 Northern California wildfires S. O’Neill et al.
371. A novel big data mining framework for reconstructing large-scale daily MAIAC AOD data across China from 2000 to 2020 B. Chen et al.
372. Impacts of abiotic and biotic factors on tundra productivity near Utqiaġvik, Alaska Q. Zhang et al.
373. Four-Decade (1980–2023) Surface Ozone Concentrations across the Contiguous United States: Fine-Resolution Estimates and Health Implications R. Liu et al.
374. Addressing Biases in Ambient PM2.5 Exposure and Associated Health Burden Estimates by Filling Satellite AOD Retrieval Gaps over India V. Katoch et al.
375. Improving the ability of solar-induced chlorophyll fluorescence to track gross primary production through differentiating sunlit and shaded leaves Z. Zhang et al.
376. Synergistic monitoring of PM2.5 and CO2 based on active and passive remote sensing fusion during the 2022 Beijing Winter Olympics S. Wang et al.
377. Downscaling aerosol optical depth by fusing satellite retrieval and model simulation using artificial intelligence technology L. Sun et al.
378. Satellite-based evaluation of AeroCom model bias in biomass burning regions Q. Zhong et al.
379. Modelling ambient PM2.5 exposure at an ultra-high resolution and associated health burden in megacity Delhi: exposure reduction target for 2030 S. Tiwari et al.
380. Opinion: Aerosol remote sensing over the next 20 years L. Remer et al.
381. Chronic Effects of High Fine Particulate Matter Exposure on Lung Cancer in China J. Li et al.
382. First close insight into global daily gapless 1 km PM2.5 pollution, variability, and health impact J. Wei et al.
383. Tracking hourly PM2.5 using geostationary satellite sensor images and multiscale spatiotemporal deep learning Z. Wang et al.
384. Influence of industrial sustainability transition on air quality in a typical resource-exhausted city J. Wang & X. Li
385. Evaluation of MODIS DT, DB, and MAIAC Aerosol Products over Different Land Cover Types in the Yangtze River Delta of China J. Jiang et al.
386. Characteristics of Remotely Sensed Urban Pollution Island (UPI) & its Linkage with Surface Urban Heat Island (SUHI) over Eastern India A. Barat & P. Parth Sarthi
387. Evaluation of ICESat-2 ATL09 Atmospheric Products Using CALIOP and MODIS Space-Based Observations K. Christian et al.
388. A CatBoost approach with wavelet decomposition to improve satellite-derived high-resolution PM2.5 estimates in Beijing-Tianjin-Hebei Y. Ding et al.
389. Features of the Extreme Fire Season of 2021 in Yakutia (Eastern Siberia) and Heavy Air Pollution Caused by Biomass Burning O. Tomshin & V. Solovyev
390. An efficient transformer-based aerosol retrieval algorithm for the polarization crossfire (PCF) satellite senor suite: development and validation> H. Gu et al.
391. An episode of transboundary air pollution in the central Himalayas during agricultural residue burning season in North India S. Khanal et al.
392. An improved method for retrieving aerosol optical depth over Ebinur Lake Basin from Gaofen-1 F. Liu & Z. Zhang
393. Difference between global and regional aerosol model classifications and associated implications for spaceborne aerosol optical depth retrieval P. Zhou et al.
394. Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak A. Rudke et al.
395. Advances in sunphotometer-measured aerosol optical properties and related topics in China: Impetus and perspectives X. Xia et al.
396. Air quality improvements can strengthen China’s food security X. Liu et al.
397. Comparison of Different Missing-Imputation Methods for MAIAC (Multiangle Implementation of Atmospheric Correction) AOD in Estimating Daily PM2.5 Levels Z. Chen et al.
398. Unveiling diurnal aerosol layer height variability from space using deep learning Y. Fan et al.
399. A general algorithm to retrieve cloud top properties by incorporating spectral characteristics and lidar measurements C. Shi et al.
400. Estimation of High-Resolution PM2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables A. Mhawish et al.
401. Influence of the Indian Summer Monsoon on Inter-Annual Variability of the Tibetan-Plateau NDVI in Its Main Growing Season X. Mao et al.
402. A Study of Air Quality in the Coalfields of NSW, Australia and Telangana, India H. Kamath et al.
403. Generating high-resolution total canopy SIF emission from TROPOMI data: Algorithm and application Z. Zhang et al.
404. Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data J. Wei et al.
405. Estimating ground-level PM2.5 using micro-satellite images by a convolutional neural network and random forest approach T. Zheng et al.
406. Data Augmentation Strategies for Improved PM2.5 Forecasting Using Transformer Architectures P. Pan et al.
407. Retrieval of total and fine mode aerosol optical depth by an improved MODIS Dark Target algorithm X. Su et al.
408. Surface water and aerosol spatiotemporal dynamics and influence mechanisms over drylands X. Chen et al.
409. Long-Term Spatiotemporal Variability and Source Attribution of Aerosols over Xinjiang, China C. Li et al.
410. Retrieval of high-resolution aerosol optical depth (AOD) using Landsat 8 imageries over different LULC classes over a city along Indo-Gangetic Plain, India R. Singh et al.
411. Characterization of Historical Aerosol Optical Depth Dynamics Using LSTM and Peak Enhancement Techniques H. Cămărășan et al.
412. Physical-Guided Transfer Deep Neural Network for High-Resolution AOD Retrieval D. Chen et al.
413. Evaluating the Utility of High-Resolution Spatiotemporal Air Pollution Data in Estimating Local PM2.5 Exposures in California from 2015–2018 L. Gladson et al.
414. Generating Hourly Fine Seamless Aerosol Optical Depth Products by Fusing Multiple Satellite and Numerical Model Data B. Zou et al.
415. Changes in leaf functional traits of rainforest canopy trees associated with an El Niño event in Borneo M. Nunes et al.
416. 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.
417. Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations A. Ukhov et al.
418. A pigment ratio index based on remotely sensed reflectance provides the potential for universal gross primary production estimation W. Wu et al.
419. Seasonality of Tropical Photosynthesis: A Pantropical Map of Correlations With Precipitation and Radiation and Comparison to Model Outputs M. Uribe et al.
420. Spatiotemporal PM2.5 estimations in China from 2015 to 2020 using an improved gradient boosting decision tree W. He et al.
421. Monitoring atmospheric particulate matters using vertically resolved measurements of a polarization lidar, in-situ recordings and satellite data over Tehran, Iran H. Panahifar et al.
422. Year (2024–25)-bound assessment of PM and Black Carbon variability over historic city in India: insights from ground-based measurements and satellite data V. Bartaria et al.
423. Improved 1-km-Resolution Hourly Estimates of Aerosol Optical Depth Using Conditional Generative Adversarial Networks L. Zhang et al.
424. Spatiotemporal Evolution Disparities of Vegetation Trends over the Tibetan Plateau under Climate Change J. Ma et al.
425. Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring Z. Li et al.
426. A Novel Aerosol Optical Depth Retrieval Method Based on SDAE from Himawari-8/AHI Next-Generation Geostationary Satellite in Hubei Province S. Deng et al.
427. Vertical Aerosol Structure Matters: Improving the AOD–PM2.5 Link for Air Quality and Exposure I. Rogozovsky et al.
428. Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud Á. Moreno-Martínez et al.
429. An improved method for retrieving aerosol optical depth using the ground-level meteorological data over the South-central Plain of Hebei Province, China F. Li et al.
430. Record-breaking aerosol levels explained by smoke injection into the stratosphere E. Hirsch & I. Koren
431. The effect of national protest in Ecuador on PM pollution R. Zalakeviciute et al.
432. Real-Time Production of High-Resolution, Gap-Free, 3-Hourly AOD over South Korea: A Machine Learning Approach Using Model Forecasts, Satellite Products, and Air Quality Data S. Kim et al.
433. Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres S. Korkin et al.
434. Long-Term (2015–2024) Daily PM2.5 Estimation in China by Using XGBoost Combining Empirical Orthogonal Function Decomposition J. Jiang et al.
435. Reprint of: Influence of trees on landscape temperature in semi-arid agro-ecosystems of East Africa L. Villani et al.
436. Improved estimation of particulate matter in China based on multisource data fusion S. Wang et al.
437. Assessment of aerosol optical depth using MAIAC and AERONET data during the 2020 wildfire season in southeastern South America M. Valle Seijo et al.
438. MAIAC Thermal Technique for Smoke Injection Height From MODIS A. Lyapustin et al.
439. Decade-low aerosol levels over the Bohai and Yellow Seas amid the COVID-19 lockdown . RunaA et al.
440. Improving the south America wildfires smoke estimates: Integration of polar-orbiting and geostationary satellite fire products in the Brazilian biomass burning emission model (3BEM) G. Pereira et al.
441. A Spatio-Temporal Weighted Filling Method for Missing AOD Values R. Gao et al.
442. Accounting for the aerosol type and additional satellite-borne aerosol products improves the prediction of PM2.5 concentrations S. Falah et al.
443. Prediction of daily mean and one-hour maximum PM2.5 concentrations and applications in Central Mexico using satellite-based machine-learning models I. Gutiérrez-Avila et al.
444. Physics-informed Bayesian telemetry for dust-aware urban BIPV fleets: Calibrated forecasting, resource-constrained operations and maintenance, and event-triggered cleaning decisions F. Bashir et al.
445. COVID-19 lockdowns cause global air pollution declines Z. Venter et al.
446. A multilevel downscaling model for enhancing nocturnal aerosol optical depth reanalysis from CAMS over the Beijing-Tianjin-Hebei region, China S. Wang et al.
447. Mapping Seasonal High-Resolution PM2.5 Concentrations with Spatiotemporal Bagged-Tree Model across China J. He et al.
448. An Investigation of Dust Activities in Southwest Baluchestan, Iran, by Synergistic use of Handheld Sunphotometer Measurements and CALIPSO-CALIOP Data A. Masoumi et al.
449. Deep Learning in Airborne Particulate Matter Sensing and Surface Plasmon Resonance for Environmental Monitoring B. Chauhan et al.
450. A gap-filling hybrid approach for hourly PM2.5 prediction at high spatial resolution from multi-sourced AOD data Q. Pu & E. Yoo
451. Satellite-based estimation of the impacts of summertime wildfires on PM2.5 concentration in the United States Z. Xue et al.
452. Three-dimensional spatiotemporal evolution of wildfire-induced smoke aerosols: A case study from Liangshan, Southwest China X. Zhang et al.
453. Long-term variations of aerosol optical depth according to satellite data and its effects on radiation and temperature in the Moscow megacity A. Poliukhov et al.
454. Impact of Urban built-up volume on Urban environment: A Case of Jakarta T. Sarker et al.
455. Handling Missing Data in Large-Scale MODIS AOD Products Using a Two-Step Model Y. Chi et al.
456. Effects of increasing spatial resolution on the spatial information content and accuracy of downward surface shortwave radiation Q. Lang et al.
457. An improved dark target method for aerosol optical depth retrieval over China from Himawari-8 L. Gao et al.
458. A Regionally Robust High-Spatial-Resolution Aerosol Retrieval Algorithm for MODIS Images Over Eastern China J. Wei et al.
459. Deriving PM2.5 from satellite observations with spatiotemporally weighted tree-based algorithms: enhancing modeling accuracy and interpretability T. Li et al.
460. Near-Time Measurement of Aerosol Optical Depth and Black Carbon Concentration at Socheongcho Ocean Research Station: Aerosol Episode Case Analysis S. Ahn et al.
461. A machine learning-based framework for high resolution mapping of PM2.5 in Tehran, Iran, using MAIAC AOD data H. Bagheri
462. A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations L. Mei et al.
463. Deep learning algorithms for prediction of PM10 dynamics in urban and rural areas of Korea H. Choi et al.
464. Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part II: Global validation and Intercomparison C. Chen et al.
465. Impact of acute exposure to ambient PM2.5 on non-trauma all-cause mortality in the megacity Delhi P. Joshi et al.
466. Where and why do conifer forests persist in refugia through multiple fire events? W. Downing et al.
467. Characterization of a seasonally snow-covered evergreen forest ecosystem Q. Zhang
468. Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model Q. Zhang et al.
469. The extreme forest fires in California/Oregon in 2020: Aerosol optical and physical properties and comparisons of aged versus fresh smoke T. Eck et al.
470. Improving XCO2 retrieval under high aerosol loads with fused satellite aerosol Data: Advancing understanding of anthropogenic emissions H. Zhu et al.
471. Solar angle matters: Diurnal pattern of solar-induced chlorophyll fluorescence from OCO-3 and TROPOMI Z. Zhang & Y. Zhang
472. Temporal and Spatial Autocorrelation as Determinants of Regional AOD-PM2.5 Model Performance in the Middle East K. Chau et al.
473. Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land A. Sayer et al.
474. Deep-learning-based post-process correction of the aerosol parameters in the high-resolution Sentinel-3 Level-2 Synergy product A. Lipponen et al.
475. Estimation of high-resolution PM2.5 concentrations based on gap-filling aerosol optical depth using gradient boosting model M. Han et al.
476. Spatial Variation and Relation of Aerosol Optical Depth with LULC and Spectral Indices V. Sharma et al.
477. Advanced algorithms on monitoring diurnal variations in dust aerosol properties using geostationary satellite imagery J. Li et al.
478. Examining the Relationship Between MODIS Satellite Aerosol Optical Depth (AOD) Data at Different Hours and PM10 Air Pollution Index in Ahvaz City M. Saeidi et al.
479. Vertical profiling of residential wood combustion aerosols over Tirana, Albania: First lidar-based observations G. Malollari et al.
480. Analysis of a saline dust storm from the Aralkum Desert – Part 1: Consistency between multisensor satellite aerosol products X. Xi et al.
481. The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis I. Rogozovsky et al.
482. Estimation of Aerosol Optical Depth at 30 m Resolution Using Landsat Imagery and Machine Learning T. Liang et al.
483. The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water J. Limbacher et al.
484. Estimation of daily PM10 and PM2.5 concentrations in Italy, 2013–2015, using a spatiotemporal land-use random-forest model M. Stafoggia et al.
485. Vegetation Angular Signatures of Equatorial Forests From DSCOVR EPIC and Terra MISR Observations X. Ni et al.
486. Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product E. Zhdanova et al.
487. Bayesian Aerosol Retrieval-Based PM2.5 Estimation through Hierarchical Gaussian Process Models J. Zhang et al.
488. An Estimation Method for PM2.5 Based on Aerosol Optical Depth Obtained from Remote Sensing Image Processing and Meteorological Factors J. Gu et al.
489. An alternative cloud index for estimating downwelling surface solar irradiance from various satellite imagers in the framework of a Heliosat-V method B. Tournadre et al.
490. Simplified and Fast Atmospheric Radiative Transfer model for satellite-based aerosol optical depth retrieval X. Yan et al.
491. Spatiotemporal Weighted for Improving the Satellite-Based High-Resolution Ground PM2.5 Estimation Using the Light Gradient Boosting Machine X. Yu et al.
492. Monitoring and simulation of a 7-day dust episode and associated dust radiative forcing over the Middle East via synergy of satellite observations, reanalysis datasets and regional/numerical models K. Mohammadpour et al.
493. Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires D. Robbins et al.
494. Application of XBAER aerosol optical depth retrieval algorithm to hyperspectral EnMAP satellite data S. Laffoy et al.
495. A Spatial Neighborhood Deep Neural Network Model for PM2.5 Estimation Across China D. Chen et al.
496. Deep Ensemble Machine Learning Framework for the Estimation of PM2.5 Concentrations W. Yu et al.
497. Evaluating the direct radiative forcing of a giant Saharan dust storm U. Rizza et al.
498. An Efficient and Accurate Model Coupled With Spatiotemporal Kalman Filter and Linear Mixed Effect for Hourly PM2.5 Mapping N. Liu et al.
499. Air quality affected by biomass burning at the Paraná River Delta on rural and industrial coastal areas of greater Rosario, Argentina M. Binet et al.
500. On the added value of satellite AOD for the investigation of ground-level PM2.5 variability J. Handschuh et al.
501. Monitoring multiple satellite aerosol optical depth (AOD) products within the Copernicus Atmosphere Monitoring Service (CAMS) data assimilation system S. Garrigues et al.
502. Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function W. Wang et al.
503. Vegetation net primary productivity in urban areas of China responded positively to the COVID-19 lockdown in spring 2020 Y. Li et al.
504. High-Resolution Modeling of Particulate Matter: Comparing SEMARA AOD and MAIAC AOD Models M. Bagherinia & S. Boudaghpour
505. Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols T. Chakraborty et al.
506. Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al.
507. Spatial-Temporal Dust Fusion Model for Integration of MODIS and WRF-Chem M. Rezvani et al.
508. Need and vision for global medium-resolution Landsat and Sentinel-2 data products V. Radeloff et al.
509. Retrieving aerosols single scattering albedo from MODIS reflectances Q. Wang et al.
510. Modeling PM2.5 concentration in tehran using satellite-based Aerosol optical depth (AOD) and machine learning: Assessing input contributions and prediction accuracy Z. Amiri & M. Zare Shahne
511. Integrating Fixed Monitoring Systems with Low-Cost Sensors to Create High-Resolution Air Quality Maps for the Northern China Plain Region C. Chao et al.
512. Effects of PM2.5 components on hypertension and diabetes: Assessing the mitigating influence of green spaces H. Sun et al.
513. Window-Based Filtering Aerosol Retrieval Algorithm of Fine-Scale Remote Sensing Images: A Case Using Sentinel-2 Data in Beijing Region J. Zhou et al.
514. Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements Y. Tong et al.
515. MODIS high-resolution MAIAC aerosol product: Global validation and analysis W. Qin et al.
516. AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America R. Dalagnol et al.
517. Spatiotemporal modeling of long-term PM2.5 concentrations and population exposure in Greece, using machine learning and statistical methods A. Kakouri et al.
518. High-Resolution Estimation of Daily PM2.5 Levels in the Contiguous US Using Bi-LSTM with Attention Z. Wang et al.
519. PM2.5 concentration estimation with 1-km resolution at high coverage over urban agglomerations in China using the BPNN-KED approach and potential application Y. Huang et al.
520. Joint Retrieval of PM2.5 Concentration and Aerosol Optical Depth over China Using Multi-Task Learning on FY-4A AGRI B. Li et al.
521. Air quality simulation with WRF-Chem over southeastern Brazil, part I: Model description and evaluation using ground-based and satellite data N. Benavente et al.
522. Long-Range Transport of Aerosols and Regional Sources Using MODIS and NASA MERRA Reanalysis Over South Asia B. Sanatan et al.
523. Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification Q. Pu & E. Yoo
524. Global modeling diurnal gross primary production from OCO-3 solar-induced chlorophyll fluorescence Z. Zhang et al.
525. Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China N. Luo et al.
526. Investigation of an Intense Dust Outbreak in the Mediterranean Using XMed-Dry Network, Multiplatform Observations, and Numerical Modeling U. Rizza et al.
527. Simultaneous retrieval of aerosol optical depth, spectral absorption and layer height from DSCOVR EPIC using MAIAC algorithm A. Lyapustin et al.
528. Advancing Exposure Assessment of PM2.5 Using Satellite Remote Sensing: A Review H. Lee
529. Uncertainty of spatial averages and totals of natural resource maps A. Wadoux & G. Heuvelink
530. A Study on Dust Storm Pollution and Source Identification in Northwestern China H. Meng et al.
531. Performance of DSCOVR/EPIC diurnal aerosol products over China: Ground validation and intercomparison L. Gui et al.
532. A model framework to reduce bias in ground-level PM2.5 concentrations inferred from satellite-retrieved AOD F. Yao & P. Palmer
533. Constraining Aerosol Phase Function Using Dual‐View Geostationary Satellites Q. Bian et al.
534. Evaluation of minerals being deposited in the Red Sea using gravimetric, size distribution, and mineralogical analysis of dust deposition samples collected along the Red Sea coastal plain I. Shevchenko et al.
535. The impact of PM2.5 on children’s blood pressure growth curves: A prospective cohort study X. Liang et al.
536. Aerosol optical depth retrieval from Geostationary Environment Monitoring Spectrometer (GEMS): Advancing the first hyperspectral geostationary air quality mission using deep learning H. Choi et al.
537. Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign M. Choi et al.
538. Spatial-Temporal Variation of AOD Based on MAIAC AOD in East Asia from 2011 to 2020 P. Wang et al.
539. High-Resolution NO2, O3, and PMs Estimation in Puglia: Leveraging AI and Explainability Techniques A. Fania et al.
540. The (mis)identification of high-latitude dust events using remote sensing methods in the Yukon, Canada: a sub-daily variability analysis R. Huck et al.
541. Changes in Aerosol Optical Depth over the Arctic Ocean as Seen by CALIOP, MAIAC, and MODIS C6.1 N. Mölders & M. Friberg
542. Remote sensing of large reservoir in the drought years: Implications on surface water change and turbidity variability of Sobradinho reservoir (Northeast Brazil) V. Martins et al.
543. Spatio-temporal modelling of PM10 daily concentrations in Italy using the SPDE approach G. Fioravanti et al.
544. Aerosol pattern changes over the dead sea from west to east - Using high-resolution satellite data S. Lee et al.
545. Constrained Retrievals of Aerosol Optical Properties Using Combined Lidar and Imager Measurements During the FIREX-AQ Campaign N. Midzak et al.
546. Assessing spatiotemporal variations of AOD in Japan based on Himawari-8 L3 V31 aerosol products: Validations and applications Y. Tan et al.
547. A Simple and Effective Random Forest Refit to Map the Spatial Distribution of NO2 Concentrations Y. Chi & Y. Zhan
548. Critical Corrections of MODIS Over-Land Aerosol Optical Depth Data From 2016 to 2017 for Near Real Time Applications X. Shen et al.
549. Retrospective assessment of pregnancy exposure to particulate matter from desert dust on a Caribbean island: could satellite-based aerosol optical thickness be used as an alternative to ground PM10 concentration? S. Tuffier et al.
550. Assessing the Nonlinear Relationship between Land Cover Change and PM10 Concentration Change in China X. Xu et al.
551. Regional monitoring of forests using the Vega-Les system: case study for Tungussko-Chunskoye forest management unit and Tunguska reserve in the Russian Krasnoyarsk region A. Kashnitskii et al.
552. Establishment of aerosol optical depth dataset in the Sichuan Basin by the random forest approach M. Jiang et al.
553. A dark target Kalman filter algorithm for aerosol property retrievals in urban environment using multispectral images G. Vivone et al.
554. Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities K. Anand et al.
555. Prediction of PM2.5 concentrations at unsampled points using multiscale geographically and temporally weighted regression N. Liu et al.
556. Spatiotemporal dynamics and exposure analysis of daily PM2.5 using a remote sensing-based machine learning model and multi-time meteorological parameters B. Chen et al.
557. Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products Z. Zhang et al.
558. Biomass burning CO, PM and fuel consumption per unit burned area estimates derived across Africa using geostationary SEVIRI fire radiative power and Sentinel-5P CO data H. Nguyen et al.
559. Quantifying PM2.5 mass concentration and particle radius using satellite data and an optical-mass conversion algorithm M. Liu et al.
560. The Spectral Nature of Earth’s Reflected Radiation: Measurement and Science Applications G. Stephens et al.
561. Aerosol Optical Depth Retrieval Over South Asia Using FY-4A/AGRI Data Y. Xie et al.
562. Estimation of particulate matter (PM2.5, PM10) concentration and its variation over urban sites in Bangladesh A. Gupta et al.
563. GOCI-II geostationary satellite hourly aerosol optical depth obtained by data-driven methods: Validation and comparison Y. Fan et al.
564. 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.
565. Full Coverage Estimation of the PM Concentration Across China Based on an Adaptive Spatiotemporal Approach C. Lei et al.
566. Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations J. Tang et al.
567. High-Resolution Satellite-Based PM2.5 Concentration Data Acquired During the COVID-19 Outbreak Throughout China: Model, Variations, and Reasons H. Guo et al.
568. High-speed rail opening and urban air quality Z. Qin et al.
569. Spatiotemporally continuous PM2.5 dataset in the Mekong River Basin from 2015 to 2022 using a stacking model D. Chen et al.
570. Comparison and evaluation of MODIS Multi-angle Implementation of Atmospheric Correction (MAIAC) aerosol product over South Asia A. Mhawish et al.
571. Connecting Crop Productivity, Residue Fires, and Air Quality over Northern India H. Jethva et al.
572. A National-Scale 1-km Resolution PM2.5 Estimation Model over Japan Using MAIAC AOD and a Two-Stage Random Forest Model C. Jung et al.
573. Characterizations of interregional transport on PM2.5 pollution in Central China with adaptive mixed effect models based on satellite observations and meteorological factors Y. Huang et al.
574. Data Integration for ML-CNPM₂.₅: A Public Sample Dataset Based on Machine Learning Models and Remote Sensing Technology Applied for Estimating Ground-Level PM₂.₅ in China Y. Fan et al.
575. Impact of aerosol layering, complex aerosol mixing, and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar, AERONET, satellite, and ground-based measurements I. Rogozovsky et al.
576. First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia Y. Cho et al.
577. Meteorological and anthropogenic contributions to changes in the Aerosol Optical Depth (AOD) over China during the last decade G. de Leeuw et al.
578. A Multiscale Land Use Regression Approach for Estimating Intraurban Spatial Variability of PM2.5 Concentration by Integrating Multisource Datasets Y. Shi et al.
579. An investigation of the impact of Canadian wildfires on US air quality using model, satellite, and ground measurements Z. Xue et al.
580. A Capsule Network Model for Aerosol Retrieval from DPC/Gaofen-5(02) Satellite Multi-Angle Polarimetric Observation H. Gu et al.
581. Direct estimates of biomass burning NOx emissions and lifetimes using daily observations from TROPOMI X. Jin et al.
582. Comprehensive reconstruction of missing aerosol optical depth in MAIAC product: A multi-layer LightGBM approach leveraging multi-scale spatio-temporal information W. Wang et al.
583. Machine learning based aerosol classification over South and East Asia using MODIS top of atmosphere reflectance and AERONET-derived clusters: A remote sensing approach M. Awais & L. Wang
584. Inversion of Aerosol Optical Depth: Incorporating Multimodel Approach X. Sun et al.
585. Aerosol optical depth over Northeastern Brazil: A multi-platform intercomparison study G. Münchow et al.
586. Spatiotemporal estimates of daily PM2.5 concentrations based on 1-km resolution MAIAC AOD in the Beijing–Tianjin–Hebei, China X. Yang et al.
587. Which model to choose? Performance comparison of statistical and machine learning models in predicting PM2.5 from high-resolution satellite aerosol optical depth P. Kulkarni et al.
588. Assessing Vertical Allocation of Wildfire Smoke Emissions Using Observational Constraints From Airborne Lidar in the Western U.S. X. Ye et al.
589. Human activity’s impact on urban vegetation in China during the COVID-19 lockdown: An atypical anthropogenic disturbance Y. Li et al.
590. Spatiotemporal modeling of PM10 via committee method with in-situ and large scale information: Coupling of machine learning and statistical methods Y. Mohammadi et al.
591. Automated Low-Cost LED-Based Sun Photometer for City Scale Distributed Measurements C. Garrido et al.
592. Spatial heterogeneity and driving factors of aerosol in Western China: Analysis on multiangle implementation of atmospheric correction–aerosol optical depth in Xinjiang over 2001–2019 W. Ma et al.
593. A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification X. Su et al.
594. An interpretable self-adaptive deep neural network for estimating daily spatially-continuous PM2.5 concentrations across China B. Chen et al.
595. Evaluation of MERRA-2 and CAMS reanalysis for black carbon aerosol in China W. Li et al.
596. June to October Aerosol Optical Depth over the Arctic at Various Spatial and Temporal Scales in MODIS, MAIAC, CALIOP and GOES Data N. Mölders & M. Friberg
597. Research on PM_2.5 Concentration Estimation Based on MAIAC AOD Spatiotemporal Supplement Data 英. 熊
598. Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research J. le Roux et al.
599. Improving the accuracy of AOD by using multi-sensors data over the Red Sea and the Persian Gulf M. Pashayi et al.
600. Estimation of Net Surface Shortwave Radiation From Remotely Sensed Data Under Dust Aerosol Conditions Y. Sun & B. Tang
601. Exploring How Aerosol Optical Depth Varies in the Yellow River Basin and Its Urban Agglomerations by Decade Y. Zhao et al.
602. SatAF-EE:An effectiveness evaluation algorithm on attack flow of satellite network B. ZHAO et al.
603. Estimating Daily PM2.5 and PM10 over Italy Using an Ensemble Model A. Shtein et al.
604. Improving discrimination between clouds and optically thick aerosol plumes in geostationary satellite data D. Robbins et al.
605. Analysis of Surface Water Trends for the Conterminous United States Using MODIS Satellite Data, 2003–2019 R. Petrakis et al.
606. Sensitivity analysis of Look-up table for satellite-based aerosol optical depth retrieval S. Amini et al.
607. Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke L. Li et al.
608. A Comparison of Multi-Angle Implementation of Atmospheric Correction and MOD09 Daily Surface Reflectance Products From MODIS A. Lyapustin et al.
609. Integrated Approach (MCD19A2 and PM10 Datasets) for Spatiotemporal Assessment of Aerosol and Revealing Approachable Predictive Model Across the Mega-Mining Region (Jharkhand), India Along with its Accuracy Measures S. Priya et al.
610. MAIAC-based climatology of atmospheric iron-oxide dust species from DSCOVR EPIC observations S. Go et al.
611. Satellite-based ground PM2.5 estimation using a gradient boosting decision tree T. Zhang et al.
612. China Surface Ozone Remote Sensing Dataset in 2021–2022 at 1 km Spatial Resolution S. Zhang et al.
613. Developing an Advanced PM2.5 Exposure Model in Lima, Peru B. Vu et al.
614. 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.
615. Predicting tropospheric nitrogen dioxide column density in South African municipalities using socio-environmental variables and Multiscale Geographically Weighted Regression S. Hlatshwayo et al.
616. The contribution of fires to PM2.5 and population exposure in the Asia Pacific region H. Lu et al.
617. Aerosol spatiotemporal dynamics, source analysis and influence mechanisms over typical drylands Y. Zhang et al.
618. Self-adaptive bandwidth eigenvector spatial filtering model for estimating PM2.5 concentrations in the Yangtze River Delta region of China H. Tan et al.
619. Global and Regional Variations and Main Drivers of Aerosol Loadings over Land during 1980–2018 J. Sun et al.
620. 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.
621. Integrating low-cost sensors, fixed and mobile monitoring with satellite data to assess the impact of biomass burning on fine, ultrafine and black carbon particle concentrations P. Krecl et al.
622. An Evaluation of Two Decades of Aerosol Optical Depth Retrievals from MODIS over Australia M. Shaylor et al.
623. MAIAC AOD profiling over the Persian Gulf: A seasonal-independent machine learning approach M. Pashayi et al.
624. PM2.5 Estimation and Spatial-Temporal Pattern Analysis Based on the Modified Support Vector Regression Model and the 1 km Resolution MAIAC AOD in Hubei, China N. Chen et al.
625. A fast and accurate radiative transfer model for aerosol remote sensing L. Mei et al.
626. Predicting ambient PM2.5 concentrations in Ulaanbaatar, Mongolia with machine learning approaches T. Enebish et al.
627. Variation of Aerosol Optical Depth Measured by Sun Photometer at a Rural Site near Beijing during the 2017–2019 Period X. Wu et al.
628. Spatial Particulate Fields during High Winds in the Imperial Valley, California F. Freedman et al.
629. Aerosol optical depth retrieval using scaled digital number (DN) values of multi-spectral satellite and a generating adversarial model based on deep learning application Y. Fan et al.
630. 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.
631. The retrieval of aerosol optical properties based on a random forest machine learning approach: Exploration of geostationary satellite images F. Bao et al.
632. High-resolution prediction of the spatial distribution of PM2.5 concentrations in China using a long short-term memory model Z. Wang et al.
633. Smoke‐Driven Changes in Photosynthetically Active Radiation During the U.S. Agricultural Growing Season K. Corwin et al.
634. Aerosols characteristics, sources, and drive factors analysis in typical megacities, NW China Z. Zhang et al.
635. Systematic Evaluation of Four Satellite AOD Datasets for Estimating PM2.5 Using a Random Forest Approach J. Handschuh et al.
636. The spatiotemporal relationship between PM2.5 and aerosol optical depth in China: influencing factors and implications for satellite PM2.5 estimations using MAIAC aerosol optical depth Q. He et al.
637. A Spatiotemporal Interpolation Graph Convolutional Network for Estimating PM₂.₅ Concentrations Based on Urban Functional Zones X. Chen et al.
638. Trends and classification of aerosol observed from MODIS sensor over Northern Europe and the Arctic K. Han et al.
639. Change in aerosol optical depth in Chinese urban agglomerations during the early phase of dual-carbon actions Y. Zheng et al.
640. Long term observations of biomass burning aerosol over Warsaw by means of multiwavelength lidar L. Janicka et al.
641. New global aerosol fine-mode fraction data over land derived from MODIS satellite retrievals X. Yan et al.
642. Enhancing the reliability of hindcast modeling for air pollution using history-informed machine learning and satellite remote sensing in China Q. He et al.
643. Characteristics of surface urban heat islands and urban aerosols over middle gangetic plains during agricultural residue burning season of post-monsoon P. Sarthi et al.
644. Application of low-cost fine particulate mass monitors to convert satellite aerosol optical depth to surface concentrations in North America and Africa C. Malings et al.
645. Deriving a Global and Hourly Data Set of Aerosol Optical Depth Over Land Using Data From Four Geostationary Satellites: GOES-16, MSG-1, MSG-4, and Himawari-8 Y. Xie et al.
646. Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations J. Yuan et al.
647. Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0) G. Ferrada et al.
648. 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.
649. Impact of COVID-19 lockdown upon the air quality and surface urban heat island intensity over the United Arab Emirates A. Alqasemi et al.