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Advances in Atmospheric Chemistry and Transportation of Aerosol by Remote Sensing and Modeling

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (15 October 2023) | Viewed by 18066

Special Issue Editors

School of atmosperhic sciences, Sun Yat-sen University, Zhuhai 519082, China
Interests: long-range transport of aerosols; the climatic effects of light-absorbing aerosols in/on snow; detection and attribution of air pollutants
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Guest Editor
College of atmosperhic sciences, Lanzhou University, Lanzhou 730000, China
Interests: physical and chemical properties; optical properties and climate effects of black carbon; dust- and other light-absorbing aerosols in snow
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Department of Geography and Atmospheric Science, University of Kansas, Lawrence, KS 66045, USA
Interests: regional climate change; dust variability; dust–climate interactions; climate modeling
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Department of Earth System Science, Tsinghua University, Beijing 100084, China
Interests: anthropogenic aerosol emissions and their climatic impacts; dust aerosols and their changes under global warming; wildfires and their climate effects; convection–cloud–precipitation–aerosol interaction
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School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China
Interests: atmospheric pollution; transboundary air pollution; aerosol–radiation interaction
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Special Issue Information

Dear Colleagues,

Aerosols emitted from natural and anthropogenic sources can be transported thousands of miles downwind and affect the regional and global environment as well as the climate system. In the atmosphere, aerosols alter the energy balance directly by absorbing and scattering both solar and terrestrial radiation and indirectly by modifying the micro- and macro-physical properties of clouds. Near the surface, aerosol particles can dramatically reduce visibility and exacerbate air quality, both of which have harmful consequences to human health. Additionally, these aerosol particles can deposit on snow/ice surfaces and then accelerate snowmelt and influence the regional hydrological and energy cycles. Therefore, quantifying the atmospheric chemistry and transportation of aerosols can provide a better understanding of their environmental and climate impacts.

To the best of our knowledge, the atmospheric chemistry and transportation of aerosols are not fully known due to a lack of measurements as well as the limitations of the physical and chemical processes of aerosols in models. Recent developments in remote sensing and Earth system models have led to substantial advances in exploring the characteristics of the atmospheric chemistry and transportation of aerosols.

This collection acts as a platform to share and investigate this topic area and provides the opportunity to quantify aerosol chemistry and transportation. This will help us to better understand the impacts of aerosols on the environment and climate.

This research topic calls for papers that can improve our understanding of the characteristics of aerosols by using satellite remote sensing and the evaluations of modeled aerosols with remote sensing. We aim to quantify the characteristics of the atmospheric chemistry and transportation of aerosols using remote sensing data, including spatial distributions, radiative effects, etc.

Potential research topics include but are not limited to the following:

  • Microphysical and optical properties of aerosols.
  • Understanding the long-range transport characteristics of aerosols.
  • The vertical distribution of aerosol species (e.g., particle mass, particle size).
  • The impacts of light-absorbing aerosols in snow/ice.
  • The interaction of aerosol–cloud–precipitation–climate.
  • The impacts of meteorological parameters on the changes in aerosol species.
  • The effect of aerosols on extreme weather.

Dr. Zhiyuan Hu
Prof. Dr. Xin Wang
Dr. Bing Pu
Dr. Yong Wang
Dr. Qiuyan Du
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • aerosol
  • aerosol species
  • optical properties
  • vertical profile
  • long-range transport
  • radiative forcing
  • light-absorbing aerosol
  • snow
  • aerosol–cloud
  • extreme weather

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Published Papers (8 papers)

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19 pages, 13951 KiB  
Article
Remote Sensing of Aerosols and Water-Leaving Radiance from Chinese FY-3/MERSI Based on a Simultaneous Method
by Xiaohan Zhang, Chong Shi, Yidan Si, Husi Letu, Ling Wang, Chenqian Tang, Na Xu, Xianqiang He, Shuai Yin, Zhihua Zhang and Lin Chen
Remote Sens. 2023, 15(24), 5650; https://doi.org/10.3390/rs15245650 - 6 Dec 2023
Cited by 3 | Viewed by 1525
Abstract
In this paper, a new simultaneous retrieval method of the SIRAW algorithm is introduced and carried out on FY3D/MERSI-II satellite images to obtain the aerosol optical thickness (AOT) and normalized water-leaving radiance (WLR) over the ocean. In order to improve the operation efficiency [...] Read more.
In this paper, a new simultaneous retrieval method of the SIRAW algorithm is introduced and carried out on FY3D/MERSI-II satellite images to obtain the aerosol optical thickness (AOT) and normalized water-leaving radiance (WLR) over the ocean. In order to improve the operation efficiency of SIRAW, a machine learning solver is developed to improve the speed of forward radiative transfer computation during retrieval. Ground-based measurement data from AERONET-OC and satellite products from VIIRS are used for comparative verification. The results show that the retrieved AOT and WLR from SIRAW are both in good agreement with those of AERONET-OC and VIIRS. Further, considering the degradation of the MERSI sensor, a new calibration scheme on 412 nm and 443 nm is adopted and an evaluation is carried out. Inter-comparison of derived WLR between MERSI and VIIRS indicates that the new calibration scheme could effectively improve the WLR retrieval accuracy of MERSI with better consistency to the official data of VIIRS. Therefore, this paper confirms that a simultaneous retrieval scheme combined with effective calibration coefficients can be used for high-precision retrieval of real aerosol and water-leaving radiation. Full article
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21 pages, 5728 KiB  
Article
Effects of Spring Dust Aerosols on Direct Radiative Forcing in China from 2000 to 2020
by Feng Wang, Minghui Qi, Shuxin Ren, Mengjie Zhu, Qianlong Xing, Mengqiang Wang, Hongquan Song, Qianfeng Wang and Pengfei Liu
Remote Sens. 2023, 15(18), 4564; https://doi.org/10.3390/rs15184564 - 16 Sep 2023
Cited by 1 | Viewed by 1532
Abstract
In order to understand the mechanism of dust aerosol influence on regional climate change, it is crucial to quantify the radiative forcing effect of dust aerosols. However, studies on the direct radiative forcing of dust aerosols over long time series in China are [...] Read more.
In order to understand the mechanism of dust aerosol influence on regional climate change, it is crucial to quantify the radiative forcing effect of dust aerosols. However, studies on the direct radiative forcing of dust aerosols over long time series in China are still lacking. The direct radiative forcing effect of dust aerosols in China over the past 20 years was simulated and evaluated based on the WRF-Chem (Weather Research and Forecasting model coupled to Chemistry) model in conjunction with remote sensing satellites and ground-based observations. The results showed that dust aerosols exhibited an obvious inter-annual positive radiative forcing effect (about 0.38 W m−2) on net radiation at the top of the atmosphere, mainly in northwest China and the North China Plain, while at the atmosphere dust aerosols presented negative radiative forcing effects on shortwave radiation and positive effects on longwave radiation, with a value of 1.54 W m−2 of net radiative forcing, showing a warming effect. Dust aerosols have a net radiative forcing value of −1.16 W m−2 at the surface, indicating a cooling effect, with a positive forcing effect on longwave radiation and a negative forcing effect on shortwave radiation, both of which coincide with the geographical distribution of dust aerosol concentrations. In terms of inter-monthly variations, at both the atmosphere and top of the atmosphere, the dust aerosols net radiative forcing values showed an increasing trend, with March (−0.20 W m−2 and 0.68 W m−2) < April (0.48 W m−2 and 1.44 W m−2) < May (0.94 W m−2 and 2.42 W m−2). Meanwhile, at the surface, the dust aerosols net radiative forcing values displayed a decreasing trend, with March (−0.88 W m−2) > April (−0.96 W m−2) > May (−1.48 W m−2). Full article
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15 pages, 8757 KiB  
Article
Summer Extreme Dust Activity in the Taklimakan Desert Regulated by the South Asian High
by Chengyun Wang, Tianhe Wang, Ying Han, Yuanzhu Dong, Shanjuan He and Jingyi Tang
Remote Sens. 2023, 15(11), 2875; https://doi.org/10.3390/rs15112875 - 1 Jun 2023
Cited by 2 | Viewed by 1763
Abstract
Summer dust aerosol in the Taklimakan Desert (TD) affects not only the albedo of the snow and ice sheets on the Tibetan Plateau (TP) but also air quality and precipitation in the downstream areas. In this study, the summer extreme dust activity in [...] Read more.
Summer dust aerosol in the Taklimakan Desert (TD) affects not only the albedo of the snow and ice sheets on the Tibetan Plateau (TP) but also air quality and precipitation in the downstream areas. In this study, the summer extreme dust activity in the TD was jointly investigated by using satellite observations and MERRA-2 reanalysis datasets and divided into two states: dust active period and dust inactive period. The horizontal and vertical distribution of summer dust during both the dust active and inactive periods, as derived from the MERRA-2 dataset, is consistent with satellite observations. By comparing the upper-level circulation and surface meteorological elements at two periods, we identify the South Asian High (SAH) as the dominant factor driving the extreme dust activity in the TD during summer. When the SAH is centered on the Iranian Plateau (IP), the dust aerosol in the TD exhibits increased activity and is lifted to higher altitudes due to significantly enhanced westerly winds, near-surface wind speed, and an ascending motion. Conversely, when the SAH is centered on the TP, the summer dust activity shows the opposite behavior. These new findings on the regulatory mechanism of the SAH on the summer dust activity in the TD are highly significant for understanding the occurrence and transport of summer Asian dust and its potential impact on heavy precipitation in the downstream areas. Full article
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39 pages, 20168 KiB  
Article
CALIOP-Based Evaluation of Dust Emissions and Long-Range Transport of the Dust from the Aral−Caspian Arid Region by 3D-Source Potential Impact (3D-SPI) Method
by Karim Abdukhakimovich Shukurov, Denis Valentinovich Simonenkov, Aleksei Viktorovich Nevzorov, Alireza Rashki, Nasim Hossein Hamzeh, Sabur Fuzaylovich Abdullaev, Lyudmila Mihailovna Shukurova and Otto Guramovich Chkhetiani
Remote Sens. 2023, 15(11), 2819; https://doi.org/10.3390/rs15112819 - 29 May 2023
Cited by 9 | Viewed by 2500
Abstract
The average monthly profiles of the dust extinction coefficient (ε) were analyzed according to the CALIOP lidar data from 2006–2021 for 24 cells (size of 2° × 5°) in the Aral-Caspian arid region (ACAR; 38–48°N, 50–70°E). Using the NOAA HYSPLIT_4 trajectory model and [...] Read more.
The average monthly profiles of the dust extinction coefficient (ε) were analyzed according to the CALIOP lidar data from 2006–2021 for 24 cells (size of 2° × 5°) in the Aral-Caspian arid region (ACAR; 38–48°N, 50–70°E). Using the NOAA HYSPLIT_4 trajectory model and the NCEP GDAS1 gridded (resolution of 1° × 1°) archive of meteorological data, the array of >1 million 10-day forward trajectories (FTs) of air particles that started from the centers of the ACAR cells was calculated. On the basis of the FT array, the average seasonal heights of the mixed layer (ML) for the ACAR cells were reconstructed. Estimates of the average seasonal dust optical depth (DOD) were obtained for ACAR’s lower troposphere, for ACAR’s ML (“dust emission layer” (EL)), and for the lower troposphere above the ML (“dust transit layer” (TL)) above each of the ACAR cells. Using the example of ACAR, it is shown that the analysis of DOD for the EL, TL and the surface layer (SL; the first 200 m AGL) makes it possible to identify dusty surfaces that are not detected on DOD diagrams for the entire atmospheric column, as well as regions where the regular transport of aged dust from remote sources can generate false sources. Based on FT array, the fields of the potential contribution of both the ACAR’s dust transit and the ACAR’s dust emission layers as well as of the entire ACAR’s lower troposphere into the DOD of the surrounding and remote regions are retrieved using the original method of potential impact of a three-dimensional source (3D-PSI). It has been found out that ACAR dust spreads over almost the entire Northern Hemisphere; the south and southeast regions of the ACAR are subject to the maximum impact of the ACAR dust. Quantitative estimates of the potential contribution of ACAR dust to the regional DODs are given for a number of control sites in the Northern Hemisphere. The results could be useful for climatological studies. Full article
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17 pages, 4899 KiB  
Article
Exploring the Spatiotemporal Variation in Light-Absorbing Aerosols and Its Relationship with Meteorology over the Hindukush–Himalaya–Karakoram Region
by Syed Shakeel Ahmad Shah, Zhongwei Huang, Ehtiram ul Haq and Khan Alam
Remote Sens. 2023, 15(10), 2527; https://doi.org/10.3390/rs15102527 - 11 May 2023
Cited by 2 | Viewed by 1648
Abstract
Light-absorbing aerosols such as black carbon (BC), organic carbon (OC), and dust can cause the warming and melting of glaciers by absorbing sunlight. Further research is needed to understand the impact of light-absorbing aerosols on the Hindukush–Karakoram–Himalaya region in northern Pakistan. Therefore, spatiotemporal [...] Read more.
Light-absorbing aerosols such as black carbon (BC), organic carbon (OC), and dust can cause the warming and melting of glaciers by absorbing sunlight. Further research is needed to understand the impact of light-absorbing aerosols on the Hindukush–Karakoram–Himalaya region in northern Pakistan. Therefore, spatiotemporal variation in absorbing surface mass concentration retrieved from Modern-Era Retrospective analysis for Research and Applications, optical properties such as aerosol optical depth (AOD) and absorption aerosol optical depth (AAOD) from the ozone monitoring instrument, and meteorological parameters from the European Centre for Medium-Range Weather Forecasts Reanalysis were investigated over northern Pakistan from 2001 to 2021. The BC concentration was lowest in May and highest in November, having a seasonal maximum peak in winter (0.31 ± 0.04 µg/m3) and minimum peak in spring (0.17 ± 0.01 µg/m3). In addition, OC concentration was found to be greater in November and smaller in April, with a seasonal higher peak in autumn (1.32 ± 0.32 µg/m3) and a lower peak in spring (0.73 ± 0.08 µg/m3). The monthly and seasonal variabilities in BC and OC concentrations are attributed to solid fuels, biomass burning, changes in vegetation, agricultural activities, and meteorology. In contrast, the dust concentration was high in July and low in December, with a seasonal average high concentration in summer (44 ± 9 µg/m3) and low concentration in winter (13 ± 2 µg/m3) due to drier conditions, dust activity, long-range transport, and human activities. Moreover, the seasonal variation in AOD and AAOD was identical and higher in the summer and lower in the winter due to dust aerosol loading and frequent dust activities. AOD and AAOD followed a similar pattern of spatial variation over the study area. Meteorological parameters greatly impact light-absorbing aerosols; therefore, low temperatures in winter increase BC and OC concentrations due to shallow boundary layers, while severe precipitation in spring decreases concentrations. During summer, dry conditions cause soil erosion and increase the amount of dust suspended in the atmosphere, leading to higher AOD and AAOD values. Conversely, higher precipitation rates and speedy winds disperse the dust aerosols in winter, resulting in lower AOD and AAOD values. Full article
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13 pages, 4004 KiB  
Article
Spatial and Temporal Variations in Spring Dust Concentrations from 2000 to 2020 in China: Simulations with WRF-Chem
by Feng Wang, Mengqiang Wang, Yunfeng Kong, Haopeng Zhang, Xutong Ru and Hongquan Song
Remote Sens. 2022, 14(23), 6090; https://doi.org/10.3390/rs14236090 - 1 Dec 2022
Cited by 4 | Viewed by 2441
Abstract
Dust emitted from arid and semi-arid areas of China is a main contributor to the global atmospheric aerosols. However, the long-term spatial and temporal variations in dust concentrations in China is still unknown. Here, we simulated the spatial and temporal variations in spring [...] Read more.
Dust emitted from arid and semi-arid areas of China is a main contributor to the global atmospheric aerosols. However, the long-term spatial and temporal variations in dust concentrations in China is still unknown. Here, we simulated the spatial and temporal variations in spring dust concentrations in China from 2000 to 2020 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The results showed that the configured WRF-Chem model in this study reproduced the spatial patterns and temporal variations of dust aerosols. The annual mean spring dust concentration at the country level was 26.95 g kg−1-dry air and showed a slightly increasing trend in China during 2000–2020. There were clear spatial differences and inter-annual variations in dust concentrations. The dust concentration generally decreased from the dust source regions of the northwest to the southeast regions of China. Obvious increasing and decreasing trends in spring dust concentrations were identified in the regions of northern Xinjiang and Gansu and in the regions of southern Xinjiang and western Inner Mongolia, respectively. In May, the dust concentration showed an increasing trend in most regions of northwestern China. This provided the basic information for insight into the long-term spatial and temporal variations in spring dust concentrations in China. Full article
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20 pages, 5245 KiB  
Article
Satellite-Observed Four-Dimensional Spatiotemporal Characteristics of Maritime Aerosol Types over the Coastal Waters of the Guangdong–Hong Kong–Macao Greater Bay Area and the Northern South China Sea
by Qihan Ma, Yingying Liu, Ting Qiu, Tingxuan Huang, Tao Deng, Zhiyuan Hu and Tingwei Cui
Remote Sens. 2022, 14(21), 5464; https://doi.org/10.3390/rs14215464 - 30 Oct 2022
Cited by 1 | Viewed by 2563
Abstract
Aerosol is important to climate and air pollution, and different aerosol types have a non-negligible impact on the environment and climate system. Based on long-term satellite lidar profiles from 2006 to 2020, the four-dimensional (x-y-z-t) spatiotemporal characteristics of different aerosol types, including clean [...] Read more.
Aerosol is important to climate and air pollution, and different aerosol types have a non-negligible impact on the environment and climate system. Based on long-term satellite lidar profiles from 2006 to 2020, the four-dimensional (x-y-z-t) spatiotemporal characteristics of different aerosol types, including clean marine (CM), dust (DU), polluted continental/smoke (PC), clean continental (CC), polluted dust (PD), elevated smoke (ES), and dusty marine (DM), over the coastal waters of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) were revealed for the first time and compared to the surrounding northern South China Sea (NSCS). (1) The dominant aerosol types in both study areas were found to be CM, ES, and DM, whose proportions summed up to more than 85%. In spring, ES was the dominant aerosol type (>40%); in other seasons, CM dominated (>34%). The proportions of anthropogenic aerosols (PC, PD, and ES) and dust-related aerosols (DU, PD, and DM) were higher in spring and winter than in summer and autumn. (2) Vertically, the number of all aerosol types declined with increasing altitude, with the exception of abnormal increase at the heights of approximately 1.5–2.8 km in spring, which was probably attributed to the effect of local and regional anthropogenic pollutants. Below the height of 2 km, the main aerosol types were CM and DM, whereas ES, PD, and DU aerosols were dominant above 2 km. (3) Horizontally, the dominant aerosol types were spatially uniform in the lower atmosphere (<2 km), while higher altitudes (especially > 4 km) showed significant horizontal heterogeneity in space. The proportion of anthropogenic aerosols over the coastal waters of the GBA was higher than that over the NSCS, due to terrestrial pollution transportation. (4) In terms of the long-term trend, the proportion of CM aerosols was found to be steadily increasing, with the anthropogenic aerosols and dust-related aerosols showing a fluctuating and decreasing trend, which resulted from the enforcement of effective air pollution control policies. Overall, the terrestrial aerosol influence tended to decrease in the study areas. The insight into aerosol types and its variation will facilitate the understanding of the aerosol climate effects and pollutant control in the coastal waters of the GBA and the NSCS. Full article
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14 pages, 4698 KiB  
Technical Note
3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China
by Zengliang Zang, Wei You, Hancheng Ye, Yanfei Liang, Yi Li, Daichun Wang, Yiwen Hu and Peng Yan
Remote Sens. 2022, 14(16), 4009; https://doi.org/10.3390/rs14164009 - 18 Aug 2022
Cited by 4 | Viewed by 2010
Abstract
Based on the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol scheme of the Weather Research and Forecasting model coupled with online Chemistry (WRF-Chem) and the three-dimensional variational (3DVAR) assimilation method, a 3DVAR data assimilation (DA) system for aerosol optical depth (AOD) [...] Read more.
Based on the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol scheme of the Weather Research and Forecasting model coupled with online Chemistry (WRF-Chem) and the three-dimensional variational (3DVAR) assimilation method, a 3DVAR data assimilation (DA) system for aerosol optical depth (AOD) and aerosol concentration observations was developed. A case study on assimilating the Himawari-8 satellite AOD and/or fine particulate matter (PM2.5) was conducted to investigate the improvement of DA on the analysis accuracy and forecast skills of the spatial distribution characteristics of aerosols, especially in the vertical dimension. The aerosol extinction coefficient (AEC) profile data from The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), surface PM2.5 and Himawari-8 AOD measurements were used for verification. One control experiment (without DA) and two DA experiments including a PM2.5 DA experiment denoted by Da_PM and a combined PM2.5 and AOD DA experiment denoted by Da_AOD_PM were conducted. Both DA experiments had positive effects on the surface PM2.5 mass concentration forecast skills for more than 60 h. However, the Da_PM showed a slight improvement in the analysis accuracy of the AOD distribution compared with the control experiment, while the Da_AOD_PM showed a considerable improvement. The Da_AOD_PM had the best positive effect on the AOD forecast skills. The correlation coefficient (CORR), root mean square error (RMSE), and mean fraction error (MFE) of the 24 h AOD forecasts for the Da_AOD_PM were 0.73, 0.38, and 0.54, which are 0.09 (14.06%), 0.08 (17.39%), and 0.22 (28.95%) better than that of the control experiment, and 0.05 (7.35%), 0.06 (13.64%), and 0.19 (26.03%) better than that of the Da_PM, respectively. Moreover, improved performance for the Da_AOD_PM occurred when the AEC profile was used for verification, as when the AOD was used for verification. The Da_AOD_PM successfully simulated the first increasing and then decreasing trend of the aerosol extinction coefficients below 1 km, while neither the control nor the Da_PM did. This indicates that assimilating AOD can effectively improve the analyses and forecast accuracy of the aerosol structure in both the horizontal and vertical dimensions, thereby compensating for the limitations associated with assimilating traditional surface aerosol observations alone. Full article
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