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The characteristics of South American biomass burning (BB) aerosols transported over northern and central Argentina were investigated from July to December 2019. This period was chosen due to the high aerosol optical depth values found in the region and because simultaneously intensive biomass burning took place over the Amazon. More specifically, a combination of remote sensing observations with simulated air parcel back trajectories was used to link the optical and physical properties of three BB aerosol events that affected Pilar Observatory (PO, Argentina, 31°41′S, 63°53′W, 338 m above sea level), with low-level atmospheric circulation patterns and with types of vegetation burned in specific fire regions. The lidar observations at the PO site were used for the first time to characterize the vertical extent and structure of BB aerosol plumes as well as their connection with the planetary boundary layer, and dust particles. Based mainly on the air-parcel trajectories, a local transport regime and a long transport regime were identified. We found that in all the BB aerosol event cases studied in this paper, light-absorbing fine-mode aerosols were detected, resulting mainly from a mixture of aging smoke and dust particles. In the remote transport regime, the main sources of the BB aerosols reaching PO were associated with Amazonian rainforest wildfires. These aerosols were transported into northern and central Argentina within a strong low-level jet circulation. During the local transport regime, the BB aerosols were linked with closer fires related to tropical forests, cropland, grassland, and scrub/shrubland vegetation types in southeastern South America. Moreover, aerosols carried by the remote transport regime were associated with a high aerosol loading and enhanced aging and relatively smaller particle sizes, while aerosols associated with the local transport pattern were consistently less affected by the aging effect and showed larger sizes and low aerosol loading. [ABSTRACT FROM AUTHOR]

Grassland fires and dust weather in Mongolia can trigger major cascading disasters. Grassland fires from autumn to the following spring can indirectly affect dust weather occurrence in the spring by affecting land surface vegetation cover. In this paper, we selected the aimag (province) of Dornod, Mongolia, a typical temperate grassland area, as the study area. The study aims to (1) analyze the spatiotemporal patterns of grassland fire and dust weather in the past 22 years, as well as the effect of grassland fire on dust weather and to (2) explore in depth the mechanisms of the effects of grassland fire on dust weather. To achieve these goals, we utilize high-resolution satellite burned-area data and Synop dust data. In general, grassland fire and dust weather occurrence clearly varied spatiotemporally across the study area. Grassland fires are typically more frequent in spring and autumn, and dust weather is mainly concentrated in spring. Cumulative grassland fires (both days and burned area) from autumn to the following spring affected the spring cumulative dust weather days significantly, especially the spring cumulative dust storm days. Analysis of the mechanism of the effect of grassland fire on dust storms showed that abundant summer precipitation resulted in higher vegetation cover and more accumulated fuel from autumn to April of the following spring. Consequently, the cumulative grassland fire days were higher, and the cumulative burned area was larger during the period, leading to a significant increase in cumulative dust storm days in May of the spring. In Mongolia, grassland fires are often caused by human factors. The findings of the present study could facilitate the crafting of measures to prevent and reduce grassland fires and indirectly minimize dust weather frequency to protect the ecological environment and promote sustainable development. [ABSTRACT FROM AUTHOR]

The Absorbing Aerosol Sensor (AAS) is carried on the Gao-Fen 5B (GF-5B) satellite, and it allows for the measurement of solar backscatter radiation by the atmosphere in the UV–Vis bands. The AAS is an imaging spectrometer that employs CCD for capturing both a continuous spectrum and the cross-track orientation with a 114° wide swath. The broad field of view provides daily global envelopment with a 4 km spatial resolution at the nadir. This paper mainly analyzes the initial working status of the instrument in orbit, including wavelength calibration, radiometric calibration, detector performance, and product availability. Preliminary observations indicate the ability of the AAS to monitor absorbing aerosols like dust, biomass burning, volcano ash, and some pollution aerosols and to identify the aerosol events in China and other regions with high spatial resolution. [ABSTRACT FROM AUTHOR]

The wintertime outbreaks of Saharan dust, increasing in intensity and frequency over the last decade, have become an important component of the global dust cycle and a challenging issue in elucidating its feedback to the ongoing climate change. For their adequate monitoring and characterization, systematic multi-instrument observations and multi-aspect analyses of the distribution and properties of desert aerosols are required, covering the full duration of dust events. In this paper, we present observations of Saharan dust in the atmosphere above Sofia, Bulgaria, during a strong dust episode over the whole of Europe in February 2021, conditioned by a persistent blocking weather pattern over the Mediterranean basin, providing clear skies and constant measurement conditions. This study was accomplished using different remote sensing (lidar, satellite, and radiometric), in situ (particle analyzing), and modeling/forecasting methods and resources, using real measurements and data (re)analysis. A wide range of columnar and range/time-resolved optical, microphysical, physical, topological, and dynamical characteristics of the detected aerosols dominated by desert dust are obtained and profiled with increased accuracy and reliability by combining the applied approaches and instruments in terms of complementarity, calibration, and normalization. Vertical profiles of the aerosol/dust total and mode volume concentrations are presented and analyzed using the LIRIC-2 inversion code joining lidar and sun-photometer data. The results show that interactive combining and use of various relevant approaches, instruments, and data have a significant synergistic effect and potential for verifying and improving theoretical models aimed at complete aerosol/dust characterization. [ABSTRACT FROM AUTHOR]

Dust emission is a common catastrophic weather phenomenon in Northern China. This phenomenon not only causes environmental problems, such as air pollution, but also has an important impact on the global dust cycle and climate change. On the basis of the dust weather observation data of 44 surface meteorological stations in the Tarim Basin from 1989 to 2021, combined with the dust aerosol optical depth (DAOD), dust surface mass concentration (DUSMASS) and wind speed data, this paper analyses the spatial and temporal dust weather characteristics in the Tarim Basin over the past 33 years. Results show that the frequency of dust weather in the Tarim Basin has declined in the past 33 years. Dust weather mainly consisted of floating dust, followed by blowing dust and dust storm. This weather had a significant seasonal change, with more dust in spring and summer and less in autumn and winter. The dust weather was mainly distributed along the south edge of the Tarim Basin and the desert hinterland of Tazhong. The spatial distribution of the dust intensity (DI) index was basically consistent with the dust weather days. Moreover, the DAOD was obviously affected by dust weather and had a significant positive correlation with the number of dust weather days and the DI, suggesting the vertical concentration of dust particles to a certain extent. Wind is also one of the most important factors affecting the release of dust. The frequency of strong wind weather decreases from the northeast to the southwest, which corresponds to the distribution of the DUSMASS. [ABSTRACT FROM AUTHOR]

The detection of drivable areas in off-road scenes is a challenging problem due to the presence of unstructured class boundaries, irregular features, and dust noise. Three-dimensional LiDAR data can effectively describe the terrain features, and a bird's eye view (BEV) not only shows these features, but also retains the relative size of the environment compared to the forward viewing. In this paper, a method called LRTI, which is used for detecting drivable areas based on the texture information of LiDAR reflection data, is proposed. By using an instance segmentation network to learn the texture information, the drivable areas are obtained. Furthermore, a multi-frame fusion strategy is applied to improve the reliability of the output, and a shelter's mask of a dynamic object is added to the neural network to reduce the perceptual delay caused by multi-frame fusion. Through TensorRT quantization, LRTI achieves real-time processing on the unmanned ground vehicle (UGV). The experiments on our dataset show the robustness and adaptability of LRTI to sand dust and occluded scenes. [ABSTRACT FROM AUTHOR]

Dust aerosols can participate in the heterogeneous nucleation process as effective ice nucleation particles, thus changing the physical properties of clouds. In this paper, we used an eye-safe 1550 nm micropulse polarization single photon lidar combined with meteorological stations, HYSPLIT backward trajectory analysis, ERA5 reanalysis data, CALIPSO, Himawari-8 and Terra-MODIS satellite data to compare the difference in cloud characteristics between dust and clean cirrus cases in Jinan from 26–29 March 2022. The study found that the aerosol affected the cloud effective radius, and the cloud top temperature impacted the properties of depolarization of dust ice clouds. According to the statistical results of the upper and lower quartiles, the depolarization ratio (DPR) range of dust cirrus on 26 March was 0.46–0.49, a similar range to the clean cirrus, while that of dust cirrus on 27 March was 0.54–0.59, which seemed much larger. Different height and temperature conditions lead to differences in the habits of ice crystals in clouds, thus changing the DPR. However, the range of the DPR between clean cirrus and dust cirrus showed no obvious difference, as the former was 0.43–0.53 and the latter was 0.46–0.59. Under the condition of higher aerosol loading, the lidar range-corrected signal (RCS) of cirrus clouds was stronger, and the cloud effective radius was 48 μm, larger than that of clean cirrus (32 μm). This may be the effect of dust on the microphysical properties of clouds. This study discusses the indirect effects of dust aerosols on cirrus clouds and the underlying mechanisms from the perspectives of microphysics and optics, which can provide more references for urban air pollution processes and aerosol-cloud interactions. [ABSTRACT FROM AUTHOR]

To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust ( τ D ) and coarse-( τ PC ) and fine-pollution particles ( τ PF ) depending on emission sources and size. Ångström exponent values are also identified separately as total and fine-mode particles ( α T and α PF ). We checked these trends in various ways; (1) first-order linear regression analysis of the annual average values, (2) percent variation using the slope of linear regression method, and (3) a reliability analysis using the Mann–Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. Although there were regional differences, τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of τ PC and τ PF , show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular, τ PF considerably decreased in Europe and Northeast Asia (95% confidential levels in MK-test), and τ PC decreased in Northeast Asia (Z-values for Seoul and Osaka are −2.955 and −2.306, respectively, statistically significant if |z| ≥ 1.96). The decrease in τ PC seems to be because of the reduction of primary and anthropogenic emissions from regulation by air quality policies. The meaningful result in this paper is that the particle size became smaller, as seen by values of α T that decreased by −3.30 to −30.47% in Europe, North Africa, and the Middle East because α T provides information on the particle size. Particle size on average became smaller over India and Asian regions considered in our study due to the decrease in coarse particles. In particular, an increase of α PF in most areas shows the probability that the average particle size of fine-mode aerosols became smaller in recent years. We presumed the cause of the increase in α T is because relatively large-sized fine-mode particles were eliminated due to air quality policies. [ABSTRACT FROM AUTHOR]

Dust outflows off Northwest Africa often propagate westward across the North Tropical Atlantic Basin (NTAB) into the greater Caribbean and US. From a health perspective, weather forecasters in these regions often monitor hazardous air quality associated with this dust. However, forecasters can be constrained by sparse data observations upwind over the Atlantic of the impacted populated areas. Global satellite sounding retrievals can potentially augment and enhance the operational forecasting toolkit for monitoring Saharan dust episodes. The focus of this paper was to examine the skill of the NOAA Unique Combined Atmospheric Processing System (NUCAPS) temperature and water vapor profiles within the dust and non-dust conditions during the March 2019 NOAA Aerosols and Ocean Science Expedition (AEROSE). During this time, the NOAA Ron Brown research ship launched radiosondes to coincide with satellite overpasses that served as independent ground truth data for evaluating NUCAPS. Compared to RAOBs from the Ron Brown, the SNPP and NOAA-20 NUCAPS-derived soundings showed skill in profiling atmospheric conditions supporting Saharan dust monitoring. Outside of dust regions, the NOAA-20 NUCAPS surface temperature bias peaks at 2.0 K; the surface water vapor bias is minimal (~1000 hPa), with a small cold bias that peaks at −50% between 742 and 790 hPa. Corresponding temperature RMS values are less than 2.0 K; water vapor RMS values are generally below 70%. Within the dust regions, NOAA-20 NUCAPS temperature soundings show a cold bias peak of 2.6 K at 918 hPa and 113% of a moist bias peak at the same level. Corresponding temperature RMS values maximize at 3.5 K at 945 hPa; the water vapor RMS shows a peak value of 106% at the same level. Weather forecasters can apply NUCAPS across the NTAB in issuing timely and accurate hazardous air quality warnings and visibility alerts to health officials and the general public. [ABSTRACT FROM AUTHOR]

In this paper, the extinction property and optical depth of charged Martian dust at infrared band 3 THz–300 THz are studied using the Mie scattering theory. It is found that the extinction coefficients of Martian atmospheric dust and the dust optical depth (DOD) of the Martian atmosphere can be amplified significantly as the dust particles are charged. This extinction amplification has a peak, called amplification resonance, which shifts toward the upper left of the r-q parameter plane with increasing frequency. Here, r denotes the particle radius and q denotes the particle's total net charge. The amplification of the Martian DOD is more significant at high altitudes than at low altitudes because the particles at high altitudes are smaller. For example, at an altitude of 30–50 km, the dust optical depth at 30 THz can be increased by 60–200%. However, at 3 THz–10 THz, the DOD at the near surface altitude (0–10 km) can still be enhanced by ~80%. This implies that by treating the Martian dust as uncharged particles, the dust density constructed from the Martian DOD data might be overestimated. The estimation error of the dust density of the Martin atmosphere may be reduced by counting the enhancement of the DOD that is caused by charged dust. [ABSTRACT FROM AUTHOR]

Dust and air pollution events are increasingly occurring around the Taklimakan Desert in southern Xinjiang and in the urban areas of northern Xinjiang. Predicting such events is crucial for the advancement, growth, and prosperity of communities. This study evaluated a dust and air pollution forecasting system based on the Weather Research and Forecasting model coupled with the China Meteorological Administration Chemistry Environment (WRF-CUACE) model using ground and satellite observations. The results showed that the forecasting system accurately predicted the formation, development, and termination of dust events. It demonstrated good capability for predicting the evolution and spatial distribution of dust storms, although it overestimated dust intensity. Specifically, the correlation coefficient (R) between simulated and observed PM10 was up to 0.85 with a mean absolute error (MAE) of 721.36 µg·m−3 during dust storm periods. During air pollution events, the forecasting system displayed notable variations in predictive accuracy across various urban areas. The simulated trends of PM2.5 and the Air Quality Index (AQI) closely aligned with the actual observations in Ürümqi. The R for simulated and observed PM2.5 concentrations at 24 and 48 h intervals were 0.60 and 0.54, respectively, with MAEs of 28.92 µg·m−3 and 29.10 µg·m−3, respectively. The correlation coefficients for simulated and observed AQIs at 24 and 48 h intervals were 0.79 and 0.70, respectively, with MAEs of 24.21 and 27.56, respectively. The evolution of the simulated PM10 was consistent with observations despite relatively high concentrations. The simulated PM2.5 concentrations in Changji and Shihezi were notably lower than those observed, resulting in a lower AQI. For PM10, the simulation–observation error was relatively small; however, the trends were inconsistent. Future research should focus on optimizing model parameterization schemes and emission source data. [ABSTRACT FROM AUTHOR]

In August 2022, China successfully launched the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS). The primary payload of this satellite is an onboard multi-beam lidar system, which is capable of observing aerosol optical parameters on a global scale. This pioneering study used the Fernald forward integration method to retrieve aerosol optical parameters based on the Level 2 data of the TECIS, including the aerosol depolarization ratio, aerosol backscatter coefficient, aerosol extinction coefficient, and aerosol optical depth (AOD). The validation of the TECIS-retrieved aerosol optical parameters was conducted using CALIPSO Level 1 and Level 2 data, with relative errors within 30%. A comparison of the AOD retrieved from the TECIS with the AERONET and MODIS AOD products yielded correlation coefficients greater than 0.7 and 0.6, respectively. The relative error of aerosol optical parameter profiles compared with ground-based measurements for CALIPSO was within 40%. Additionally, the correlation coefficients R2 with MODIS and AERONET AOD were approximately between 0.5 and 0.7, indicating the high accuracy of TECIS retrievals. Utilizing the TECIS retrieval results, combined with ground air quality monitoring data and HYSPLIT outcomes, a typical dust transport event was analyzed from 2 to 7 April 2023. The results indicate that dust was transported from the Taklamakan Desert in Xinjiang, China, to Henan and Anhui provinces, with a gradual decrease in the aerosol depolarization ratio and backscatter coefficient during the transport process, causing varying degrees of pollution in the downstream regions. This research verifies the accuracy of the retrieval algorithm through multi-source data comparison and demonstrates the potential application of the TECIS in the field of aerosol science for the first time. It enables the fine-scale regional monitoring of atmospheric aerosols and provides reliable data support for the three-dimensional distribution of global aerosols and related scientific applications. [ABSTRACT FROM AUTHOR]

Between 14 March and 21 April 2022, an extensive investigation of an extraordinary Saharan dust intrusion over Europe was performed based on lidar measurements obtained by the European Aerosol Research Lidar Network (EARLINET). The dust episode was divided into two distinct periods, one in March and one in April, characterized by different dust transport paths. The dust aerosol layers were studied over 18 EARLINET stations, examining aerosol characteristics during March and April in four different regions (M-I, M-II, M-III, and M-IV and A-I, A-II, A-III, and A-IV, respectively), focusing on parameters such as aerosol layer thickness, center of mass (CoM), lidar ratio (LR), particle linear depolarization ratio (PLDR), and Ångström exponents (ÅE). In March, regions exhibited varying dust geometrical and optical properties, with mean CoM values ranging from approximately 3.5 to 4.8 km, and mean LR values typically between 36 and 54 sr. PLDR values indicated the presence of both pure and mixed dust aerosols, with values ranging from 0.20 to 0.32 at 355 nm and 0.24 to 0.31 at 532 nm. ÅE values suggested a range of particle sizes, with some regions showing a predominance of coarse particles. Aerosol Optical Depth (AOD) simulations from the NAAPS model indicated significant dust activity across Europe, with AOD values reaching up to 1.60. In April, dust aerosol layers were observed between 3.2 to 5.2 km. Mean LR values typically ranged from 35 to 51 sr at both 355 nm and 532 nm, while PLDR values confirmed the presence of dust aerosols, with mean values between 0.22 and 0.31 at 355 nm and 0.25 to 0.31 at 532 nm. The ÅE values suggested a mixture of particle sizes. The AOD values in April were generally lower, not exceeding 0.8, indicating a less intense dust presence compared to March. The findings highlight spatial and temporal variations in aerosol characteristics across the regions, during the distinctive periods. From 15 to 16 March 2022, Saharan dust significantly reduced UV-B radiation by approximately 14% over the ATZ station (Athens, GR). Backward air mass trajectories showed that the dust originated from the Western and Central Sahara when, during this specific case, the air mass trajectories passed over GRA (Granada, ES) and PAY (Payerne, CH) before reaching ATZ, maintaining high relative humidity and almost stable aerosol properties throughout its transport. Lidar data revealed elevated aerosol backscatter (baer) and PLDR values, combined with low LR and ÅE values, indicative of pure dust aerosols. [ABSTRACT FROM AUTHOR]

Haze aerosols have a profound impact on air quality and pose serious health risks to the public. Due to its geographical location, Beijing experienced haze events in the spring of 2024. Lidar is an active remote sensing technology with a high spatiotemporal resolution and the ability to classify aerosols, and it is essential for effective haze monitoring. This study utilizes fluorescence–Raman–Mie polarization lidar with an emission wavelength of 355 nm, employing the δ p - G f method based on the particle depolarization ratio at 355 nm ( δ p 355 ) and the fluorescence capacity ( G f ), and combines meteorological data and backward-trajectory analysis to observe and classify low-altitude haze aerosols in Beijing during the spring of 2024. Notably, a mining dust event with strong fluorescence backscatter was detected. The haze aerosols were categorized into three types: pollution aerosols, desert dust, and mining dust. Their optical properties were summarized and compared. Desert dust showed a particle depolarization ratio range of 0.23–0.39 and a fluorescence capacity range from 0.18 × 10−4 to 0.63 × 10−4. Pollution aerosols had a larger fluorescence capacity but a lower depolarization ratio compared to desert dust, with a fluorescence capacity ranging from 0.55 × 10−4 to 1.10 × 10−4 and a depolarization ratio ranging from 0.10 to 0.17. Mining dust shared similar depolarization characteristics with desert dust but had a larger fluorescence capacity, ranging from 0.71 × 10−4 to 1.23 × 10−4, with a depolarization ratio range of 0.30–0.39. This study validates the effectiveness of the δ p 355 - G f method in classifying low-altitude haze aerosols in Beijing. Additionally, it offers a new perspective for more detailed dust classification using lidar. Furthermore, utilizing the δ p 355 - G f classification method and the δ p 355 - G f distributions of three typical aerosol samples, we developed a set of equations for the analysis of mixed aerosols. This method facilitates the separation and fraction analysis of aerosol components under various mixing scenarios. It enables the characterization of variations in the three types of haze aerosols at different altitudes and times, offering valuable insights into the interactions between desert dust, mining dust, and pollution aerosols in Beijing. [ABSTRACT FROM AUTHOR]

The advancement of more precise remote sensing inversion technology for dust aerosols has long been a hot topic in the field of the atmospheric environment. In 2023, China experienced 18 dust-related weather events, predominantly in spring. These high-intensity and frequent dust events have attracted considerable attention. However, gridded observation data of dust intensity levels are not collected in current dust monitoring and forecasting operations. Based on the Himawari 9 geostationary satellite data, this study establishes a new method to identify spring dust events. This method integrates the brightness temperature difference method and the multiple infrared dust index, taking into account the response discrepancies of the multiple infrared dust index under various underlying surfaces. Furthermore, by obtaining dynamic background brightness temperature values eight times a day, threshold statistics are applied to analyze the correlation between the infrared difference dust index and ground-observed dust level, so as to establish a satellite-based near-surface dust intensity level identification algorithm. This algorithm aims to improve dust detection accuracy, and to provide more effective gridded observation support for dust forecasting and monitoring operations. The test results indicate that the algorithm can effectively identify the presence or absence of dust, with a misjudgment rate of less than 3%. With regard to dust intensity, the identification of blowing sand and floating dust aligns relatively well with ground-based observations, but notable uncertainties exist in determining a dust intensity of sand-storm level or above. Among these uncertainties, the differences between ground-based observations and satellite identification caused by non-grounded dust in the upper air, and the selection of dust identification thresholds, are two important error sources in the dust identification results of this study. [ABSTRACT FROM AUTHOR]

Dust aerosols serve as a crucial nutrient source to the oceans and profoundly influence marine ecosystems. This study used satellite and ground observations to explore a strong dust event on 9–13 April 2023, emanating from the Gobi Desert, shared by Mongolia and China's Inner Mongolia region. We investigated the deposition of dust particles and their effects on marine phytoplankton communities. Our findings revealed that the dust event was intense, enduring, and expansive, illustrated by hourly PM10 concentrations peaking at 5055 µg/m3 near the source and consistently exceeding 1000 µg/m3, even at considerable distances. The dust traveled along two different trajectories and was deposited in the same area of the Northwest Pacific. Total dust deposition in the study area (37°N–42°N, 145°E–165°E) was 79.88 mg/m2 from 13 to 18 April, much higher than the 2019–2022 average deposition of 33.03 mg/m2 for the same period. With dust deposition, the observed mean chlorophyll-a concentrations in the area increased to 2.78 mg/m3 on 14 April, an extraordinary 692% increase above the long-term average. These results highlight the profound impact of dust on the productivity of marine phytoplankton communities by inputting more nutrients into the ocean through different pathways. [ABSTRACT FROM AUTHOR]

During 14–16 March 2021, a large-scale dust storm event occurred in the northern region of China, and it was considered the most intense event in the past decade. This study employs observation data for PM2.5 and PM10 from the air quality monitoring station, the HYSPLIT model, ground-based polarized Lidar networks, AGRI payload data from Fengyun satellites and CALIPSO satellite Lidar data to jointly explore and scrutinize the three-dimensional spatial and temporal characteristics of aerosol transport. Firstly, by integrating meteorological data for PM2.5 and PM10, the air quality is assessed across six stations within the Lidar network during the dust storm. Secondly, employing a backward trajectory tracking model, the study elucidates sources of dust at the Lidar network sites. Thirdly, deploying a newly devised portable infrared 1064 nm Lidar and a pulsed 532 nm Lidar, a ground-based Lidar observation network is established for vertical probing of transboundary dust transport within the observed region. Finally, by incorporating cloud imagery from Fengyun satellites and CALIPSO satellite Lidar data, this study revealed the classification of dust and the height distribution of dust layers at pertinent sites within the Lidar observation network. The findings affirm that the eastward movement and southward compression of the intensifying Mongolian cyclone led to severe dust storm weather in western and southern Mongolia, as well as Inner Mongolia, further transporting dust into northern, northwestern, and northeastern parts of China. This dust event wielded a substantial impact on a broad expanse in northern China, manifesting in localized dust storms in Inner Mongolia, Beijing, Gansu, and surrounding areas. In essence, the dust emanated from the deserts in Mongolia and northwest China, encompassing both deserts and the Gobi region. The amalgamation of ground-based and spaceborne Lidar observations conclusively establishes that the distribution height of dust in the source region ranged from 3 to 5 km. Influenced by high-pressure systems, the protracted transport of dust over extensive distances prompted a gradual reduction in its distribution height owing to sedimentation. The comprehensive analysis of pertinent research data and information collectively affirms the precision and efficacy of the three-dimensional aerosol monitoring conducted by the ground-based Lidar network within the region. [ABSTRACT FROM AUTHOR]

This Special Issue lists nine publications, covering the topics of advanced atmospheric lidar techniques, lidar retrievals, and lidar applications. The investigations listed here are diverse, but they are all focused on atmospheric lidars. Some urgent issues, for instance low blind zone detection and polarization detection at a near-infrared wavelength band, were discussed and explored. The results are helpful for extending atmospheric lidar applications. In terms of lidar retrievals, a planetary boundary layer height retrieval and an automatic lidar retrieval for aerosol optical properties were investigated in some of the publications, which can strengthen the atmospheric lidar capabilities. For lidar applications, a detailed analysis of the evolution of stratospheric aerosol and dust–cloud interactions was presented. In this Editorial, the articles published within this Special Issue are reviewed to highlight their innovative contributions and main research findings. [ABSTRACT FROM AUTHOR]

Different aerosol types exhibit distinct radiative effects in different regions, attributed to their unique optical characteristics and regional distributions. This study focuses on North China, which is impacted by both natural and anthropogenic aerosols with high concentrations and a variety of aerosol types. While many studies on aerosol direct radiative effects have been conducted in this region, the majority have focused on a specific type of aerosol or overall aerosol, leaving limited research on the direct radiative effects and contributions of different aerosol types. In this study, we use CALIPSO satellite data from 2011 to 2020 to investigate concentrations and distributions of different aerosol types. The results reveal that dust, polluted dust, polluted continental/smoke, and elevated smoke are the dominant aerosol types in North China. Based on the radiative closure experiment, we systematically calculate the radiative effects of different aerosol types and their corresponding contributions to the energy budget by combining satellite data with the Fu–Liou radiative transfer model. The annual average net aerosol direct radiative effect (ADRE) of North China is −6.1 and −13.43 W m−2 at the TOA and surface, respectively, causing a net warming effect of 7.33 W m−2 in the atmosphere. For each main aerosol type, dust contributes 93% to the shortwave ADRE in the western dust source region, while polluted dust mainly contributes 31% and 45% of the total ADRE, in Northwest China and North China Plain, respectively. Anthropogenic pollutant aerosols account for 58% of the total ADRE in Northeast China. This study holds great significance in elucidating the dominant aerosol types and their concentrations in North China, comprehending the impacts of different aerosol types on the local energy balance. [ABSTRACT FROM AUTHOR]

Aerosol optical depth (AOD) at night-time has become a hot topic in recent years due to the development of new instruments recording accurate ground-based lunar irradiance measurements, and the development of calibration methods and extraterrestrial irradiance models adapted to lunar photometry. This study uses all daytime and night-time AOD data available at Valladolid (Spain) from October 2016 to March 2022 in order to analyze its behavior and the added contribution of night data. The annual, monthly and daily AOD evolution is studied comparing daytime and night-time values and checking the correlation between them. For this purpose, the daily averages are computed, showing an annual pattern, with low AOD values throughout the year (mean value of AOD at 440 nm: 0.122), where winter months have the lower and summer the higher values, as observed in previous studies. All these AOD values are modulated by frequent desert dust events over the Iberian Peninsula, with a strong influence on daily and monthly mean values in February and March, where the strongest desert outbreaks occurred. The added new data confirm these results and the good correlation between daytime and night-time data. Also, a complete daily evolution is shown, observing that AOD and Ångström exponent (AE) mean values vary by only ±0.02 in 24 h, with a maximum value at 06:00 UTC and minimum at 18:00 UTC for both parameters. [ABSTRACT FROM AUTHOR]

Dust impact on lake surface water temperature (SWT) over lakes, located in the Eastern Mediterranean, has not yet been discussed in previous publications. We investigated the effect of an extreme dust intrusion on the diurnal behavior of SWT in Lake Kinneret, appearing from 7–9 September 2015. This was carried out using METEOSAT and in-situ observations of SWT. In the presence of dust, METEOSAT SWT decreased along with increasing dust pollution both in the daytime and nighttime. This contradicted in-situ measurements of SWT at a depth of 20 cm which increased to 1.2 °C in the daytime and to 1 °C in the nighttime, compared to SWT on clear-sky September 6. The in-situ radiometer measurements of upwelling longwave radiation (ULWR) provided us with a criterion for assessing the reliability of METEOSAT and in-situ observations of SWT. Using this criterion, we found that, in the presence of dust, in-situ SWT was in line, whereas METEOSAT SWT contradicted in-situ ULWR. Considering in-situ ULWR is determined by actual SWT, we concluded that, in the presence of dust, in-situ SWT were capable of reproducing Kinneret SWT, while METEOSAT was incapable of doing so. An observed increase in daytime air temperature during the dust intrusion contributed to an increase in daytime Kinneret SWT. In the presence of maximal dust pollution on September 8, atmospheric humidity (ρv) exceeded by 30% that on clear-sky September 6. This increase in ρv was observed in the absence of moisture advection indicating that dust intrusion can cause additional evaporation from Lake Kinneret and, consequently, intensify its drying up. [ABSTRACT FROM AUTHOR]

Dust storms are one of the major causes of the destruction of natural ecosystems and human infrastructure worldwide. Therefore, the identification and mapping of susceptible regions to dust storm formation (SRDSFs) is of great importance. Determining SRDSFs by considering the concept of risk in the decision-making process and the kind of manager's attitude and planning can be very valuable in dedicating financial resources and time to identifying and controlling the negative impacts of SRDSFs. The purpose of this study was to present a new risk-based method in decision making to create SRDSF maps of pessimistic and optimistic scenarios. To achieve the purpose of this research, effective criteria obtained from various sources were used, including simulated surface data, satellite products, and soil data of Saudi Arabia. These effective criteria included vegetation cover, soil moisture, soil erodibility, wind speed, precipitation, and absolute air humidity. For this purpose, the ordered weighted averaging (OWA) model was employed to generate existing SRDSF maps in different scenarios. The results showed that the wind speed and precipitation criteria had the highest and lowest impact in identifying dust centers, respectively. The areas identified as SRDSFs in very pessimistic, pessimistic, neutral, optimistic, and very optimistic scenarios were 85,950, 168,275, 255,225, 410,000, and 596,500 km2, respectively. The overall accuracy of very pessimistic, pessimistic, neutral, optimistic, and very optimistic scenarios were 84.1, 83.3, 81.6, 78.2, and 73.2%, respectively. The very pessimistic scenario can identify the SRDSFs in the study area with higher accuracy. The overall accuracy of the results of these scenarios compared to the dust sources obtained from the previous studies were 92.7, 94.2, 95.1, 88.4, and 79.7% respectively. The dust sources identified in the previous studies have a higher agreement with the results of the neutral scenario. The proposed method has high flexibility in producing a wide range of SRDSF maps in very pessimistic to very optimistic scenarios. The results of the pessimistic scenarios are suitable for risk-averse managers with limited financial resources and time, and the results of the optimistic scenarios are suitable for risk-taking managers with sufficient financial resources and time. [ABSTRACT FROM AUTHOR]

Atmospheric particulate matter (PM) is a major air pollutant. PM2.5 and PM10 pose particularly serious threats to the ecological environment and human health. Vegetation plays an important role in reducing the concentration of particles. Based on a long time series of air quality, meteorological, and vegetation coverage data in the Beijing–Tianjin–Hebei (BTH) region, the present paper evaluated the influence at the overall and built-up area scales and quantified the process involved in the dry settlement of particles on vegetation based on a mathematical model. The experimental results showed that (1) the total amounts of PM10 reduced by vegetation in the BTH area were 505,200 t, 465,500 t, 477,200 t and 396,500 t in 2015, 2016, 2017 and 2018, respectively, and the total amount of PM2.5 was reduced by 19,400 t, 19,200 t, 16,400 t and 12,700 t, respectively. The annual reduction in PM10 and PM2.5 from 2015 to 2018 by vegetation in the BTH region showed a downwards trend, and the annual reduction was mainly caused by the significant decrease in PM concentration. (2) More than 80% of the reduction in annual yield was concentrated in May–September, and a large leaf area was the main reason for the largest yield reduction in the growing season. The efficiency of PM reduction in forestland was approximately five–seven times that in grassland, and the deciduous broad-leaved forest was the main driver of this reduction in each forest. (3) The reduction in PM10 by vegetation was approximately 30 times that of PM2.5. However, the reduction in PM2.5 by vegetation should not be ignored because PM2.5 has a stronger correlation with human production and living activities. Increasing the area and density of green space via afforestation, returning farmland to forest and giving full play to the self-purification function of green spaces are very important to reducing and controlling the concentration of PM. [ABSTRACT FROM AUTHOR]

This paper evaluates the use of the 'Dust red/green/blue (RGB)' product derived from Spinning Enhanced Visible and Infrared Imager (SEVIRI) data at 15-min, 30-min, and 60-min temporal resolutions, for monitoring dust emissions in the Middle East. From January 2006 to December 2006, observations of dust emission point sources were recorded at each temporal resolution across the Middle East. Previous work has demonstrated that using SEVIRI data is a major improvement on other remote sensing methods for mapping dust sources in the Sahara, by enabling dust-storm observations through sequential images, back to the point of first emission. However, the highest temporal resolution available (15-min observations) produces 96 images per day, resulting in significantly higher data management requirements than data provided at 30-min and 60-min intervals. To optimize future research workflows, this paper investigates the effect of lowering the temporal resolution on the number and spatial distribution of observed dust emission events in the Middle East. The results show that the number of events observed reduced by 17% for 30-min resolution and 50% for 60-min resolution. These differences change seasonally, with the highest reduction observed in summer (34% and 64% reduction, respectively). [ABSTRACT FROM AUTHOR]

A detection algorithm of dust and smoke for application to satellite multi-channel imagers is introduced in this paper. The algorithm is simple and solely based on spectral and spatial threshold tests along with some uniformity texture. Detailed examinations of the threshold tests are performed along with explanations of the physical basis. The detection is performed efficiently at the pixel level and output is in the form of an index (or flag): 0 (no dust/smoke) and 1 (dust/smoke). The detection algorithm is implemented sequentially and designed to run on segments of data instead of pixel by pixel for efficient processing. MODIS observations are used to test the operation and performance of the algorithm. The algorithm can capture heavy dust and smoke plumes very well over both land and ocean and therefore is used as a global detection algorithm. The method can be applied to any multi-channel imagers with channels at (or close to) 0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 μ?m (such as current EOS/MODIS and future JPSS/VIIRS and GOES-R/ABI) for the detection of dust and smoke. It can be used to operationally monitor the outbreak and dispersion of dust storms and smoke plumes that are potentially hazardous to our environment and impact climate. [ABSTRACT FROM AUTHOR]

In land battlefield environments, aerosol particles can cause laser beams to undergo attenuation, thus deteriorating the operational performance of military laser devices. The particle size distribution (PSD) and extinction coefficient are key optical properties for assessing the attenuation characteristics of laser beams caused by aerosol particles. In this study, we employed the laser diffraction method to measure the PSDs of graphite smoke screen, copper powder smoke screen, iron powder smoke screen, ground dust, and soil explosion dust. We evaluated the goodness of fit of six common unimodal PSD functions and a bimodal lognormal PSD function employed for fitting these aerosol particles using the root mean square error (RMSE) and adjusted R2, and selected the optimal PSD function to evaluate their extinction coefficients in the laser wavelength range of 0.249~12 μm. The results showed that smoke screens, ground dust, and soil explosion dust exhibited particle size ranges of 0.7~50 µm, 1~400 µm, and 1.7~800 μm, respectively. The lognormal distribution had the best goodness of fit for fitting the PSDs of these aerosol particles in the six unimodal PSD functions, followed by the gamma and Rosin–Rammler distributions. For the bimodal aerosol particles with a lower span, the bimodal lognormal PSD functions exhibited the best goodness of fit. The graphite smoke screen exhibited the highest extinction coefficient, followed by the copper and iron powder smoke screens. In contrast, the ground dust and soil explosion dust exhibited the lowest extinction coefficients, reaching their minimum values at a wavelength of approximately 8.2 μm. This study provides a basis for analyzing and improving the detection and recognition performance of lasers in land battlefield environments. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Extreme weather events are happening more frequently as a result of global climate change. Dust storms broke out in the spring of 2017 in China and drastically impacted the local air quality. In this study, a variety of data, including aerosol vertical profiles, surface particle concentration, meteorological parameters, and MODIS–derived aerosol optical depth, as well as backward trajectory analysis, were employed to analyze two dust events from April to May in Beijing. The dust plumes were mainly concentrated below 0.8 km, with peak PM10 values of 1000 μg·m−3 and 300 μg·m−3 in the two cases. The aerosols showed different vertical distribution characteristics. The pure dust in case 1 from 4 to 5 May 2017 had a longer duration (2 days) and presented a larger aerosol extinction coefficient (2.27 km−1 at 355 nm and 1.25 km−1 at 532 nm) than that of the mixed dust in case 2 on 17 April 2017 (2.01 km−1 at 355 nm and 1.33 km−1 at 532 nm). The particle depolarization ratio (PDR) remained constant (0.24 ± 0.03 in case 1) from the surface to 0.8 km in height. In contrast, the PDR profile in the mixed dust (case 2) layer was split into two regions—large values exceeding 0.15 above 0.6 km and small values of 0.11 ± 0.03 below 0.6 km. The influence of meteorological information on aerosol distribution was also investigated, and wind was predominant through the observing period. The pure dust in case 1 was mainly from Mongolia, with strong northwest winds, while the near-surface mixed pollution was caused by the combination of long-transported sand and local emission. Furthermore, lidar-derived profiles of dust mass concentrations in the two cases were presented. This study reveals the vertical characteristics of dust aerosols in the production and dissipation of localized dust events and confirms the efficacy of thorough observations with multiple approaches from the ground to space to monitor dust events in real time. [ABSTRACT FROM AUTHOR]

The atmospheric dust is an important factor in the evolution of the Martian climate and has a major impact on the scientific exploration of the Martian lander or rover and its payload. This paper used remote sensing images to calculate atmospheric optical depth that characterizes the spatial distribution of the atmospheric dust of Mars. The optical depth calculated by the images of the High Resolution Imaging Science Experiment (HiRISE) in the inspection area of the Spirit rover had a similar temporal variation to the optical depth directly measured by the Spirit rover from the sunlight decay. We also used the HiRISE images to acquire the seasonal variation of optical depths in the candidate landing area of China's Mars Mission (Tianwen-1). The results have shown that the seasonal pattern of the optical depth in the candidate landing area is consistent with the dust storm sequences in this area. After Tianwen-1 enters the orbit around Mars, the images collected by the Moderate Resolution Imaging Camera (MoRIC), and the High Resolution Imaging Camera (HiRIC) can be used to study the atmospheric optical depth in the candidate landing area, providing reference for the safe landing and operation of the lander and rover. [ABSTRACT FROM AUTHOR]

Smoke from fires significantly influences climate, weather, and human health. Fire smoke is traditionally detected using an aerosol index calculated from spectral contrast changes. However, such methods usually miss thin smoke plumes. It also remains challenging to accurately separate smoke plumes from dust, clouds, and bright surfaces. To improve smoke plume detections, this paper presents a new scattering-based smoke detection algorithm (SSDA) depending mainly on visible and infrared imaging radiometer suite (VIIRS) blue and green bands. The SSDA is established based on the theory of Mie scattering that occurs when the diameter of an atmospheric particulate is similar to the wavelength of the scattered light. Thus, smoke commonly causes Mie scattering in VIIRS blue and green bands because of the close correspondence between smoke particulate diameters and the blue/green band wavelengths. For developing the SSDA, training samples were selected from global fire-prone regions in North America, South America, Africa, Indonesia, Siberia, and Australia. The SSDA performance was evaluated against the VIIRS aerosol detection product and smoke detections from the ultraviolet aerosol index using manually labeled fire smoke plumes as a benchmark. Results show that the SSDA smoke detections are superior to existing products due chiefly to the improved ability of the algorithm to detect thin smoke and separate fire smoke from other surface types. Moreover, the SSDA smoke distribution pattern exhibits a high spatial correlation with the global fire density map, suggesting that SSDA is capable of detecting smoke plumes of fires in near real-time across the globe. [ABSTRACT FROM AUTHOR]

In this paper, we present long-term observations of the multiwavelength Raman lidar Polly X T conducted in the framework of the DACAPO-PESO campaign. Regardless of the relatively clean atmosphere in the southern mid-latitude oceans region, we regularly observed events of long-range transported smoke, originating either from regional sources in South America or from Australia. Two case studies will be discussed, both identified as smoke events that occurred on 5 February 2019 and 11 March 2019. For the first case considered, the lofted smoke layer was located at an altitude between 1.0 and 4.2 km, and apart from the predominance of smoke particles, particle linear depolarization values indicated the presence of dust particles. Mean lidar ratio values at 355 and 532 nm were 49 ± 12 and 24 ± 18 sr respectively, while the mean particle linear depolarization was 7.6 ± 3.6% at 532 nm. The advection of smoke and dust particles above Punta Arenas affected significantly the available cloud condensation nuclei (CCN) and ice nucleating particles (INP) in the lower troposphere, and effectively triggered the ice crystal formation processes. Regarding the second case, the thin smoke layers were observed at altitudes 5.5–7.0, 9.0 and 11.0 km. The particle linear depolarization ratio at 532 nm increased rapidly with height, starting from 2% for the lowest two layers and increasing up to 9.5% for the highest layer, indicating the possible presence of non-spherical coated soot aggregates. INP activation was effectively facilitated. The long-term analysis of the one year of observations showed that tropospheric smoke advection over Punta Arenas occurred 16 times (lasting from 1 to 17 h), regularly distributed over the period and with high potential to influence cloud formation in the otherwise pristine environment of the region. [ABSTRACT FROM AUTHOR]

Dust in sand dunes is an effective and important source of dust emission. The Taklimakan Desert (TD) is one of the main sources of global dust: the sand dunes account for approximately 85% of the total area of the TD. However, the dust concentration, emission characteristics, and physical factors of different parts of the sand dunes in the TD during the day and night, as well as dust and non-dust days, remain unclear. In this study, dust observations were collected over a 3 month period in the TD to investigate the physical processes by which dust moves across a surface and generates PM10 and PM2.5 from the top and bottom of sand dunes. The results showed that the daily average maximum concentrations of particulate matter with diameters below 2.5 and 10 µm (PM2.5 and PM10) in the dune during the observation period reach ~90 and ~190 µg·m−3, respectively. Dust emission generated in the saltation process (maximum emission of PM10 was 3–5 mg·m−2·s−1) in the TD dunes was larger than that in other areas and had a good correlation with u* (friction velocity), where u* = 0.4 m·s−1 was the threshold of sand dune dust emission. The wind speed at the top of dunes was larger than that at the bottom, which was conducive to the accumulation of PM10 at the top of the dune. Furthermore, the MLH (mixed layer height) decreased after sunset and the turbulence weakens, which was conducive to the retention of dust in the air. Moreover, the dust made the solar radiation at the top of the dune −15 W·m−2 (average) lower than at the bottom. These results provided a new understanding of dune emissions in the TD and could be used for dust modeling in regional and global models. [ABSTRACT FROM AUTHOR]

The Hapke two-layer medium model is an efficient way of simulating the spectra of dusty leaves. However, the simulation accuracy is low when the amount of dustfall is small. To solve this problem, we introduced the dust coverage factor and the linear spectral mixing model, to improve the accuracy of the Hapke two-layer medium model. Firstly, based on the assumption of spherical dust particles, the arrangement and accumulation mode of the particles were set, and the coverage factor and accumulation thickness of particles in the leaf area were calculated. Then, the coverage factor was used as an abundance. Endmembers were the spectra of dust-free leaves (measured) and dust-covered leaves (simulated by model), and the final simulated spectra were calculated using linear spectral mixing theory. This study presents the following findings: (1) When the coverage factor was calculated using the exponential model, the maximum difference between the corrected simulated spectra and the measured spectra was 3.4%, and the maximum difference between the original simulated spectra and the measured spectra was 15.2%. The accuracy of the corrected spectra is much higher than that of the original simulated spectra. (2) In this study, the physical thickness and optical thickness calculated by the Hapke two-layer medium model are equivalent, which is quite different from the actual dust accumulation. When the linear spectral mixing model is introduced, to modify the simulation value when the number of dust particles accumulated is less than one layer, the spectral endmember value of the simulated dust leaf is replaced by the simulation spectrum when the number of dust particles accumulated is exactly one layer. The calculated cor-rection spectrum has high rationality and credibility. This finding may be beneficial for monitoring amounts of dustfall accurately using remote sensing in mining areas. [ABSTRACT FROM AUTHOR]

The vertical aerosol layering of the troposphere is poorly documented in mountainous regions, particularly in the Alpine valleys, which are influenced by valley and mountain winds. To improve our knowledge of particulate matter trapped in the Annecy valley, synergetic measurements performed by a ground-based meteorological Raman lidar and a Rayleigh-Mie lidar aboard an ultralight aircraft were implemented as part of the Lacustrine-Water vApor Isotope inVentory Experiment (L-WAIVE) over Lake Annecy. These observations were complemented by satellite observations and Lagrangian modeling. The vertical profiles of aerosol optical properties (e.g., aerosol extinction coefficient (AEC), lidar ratio (LR), particle linear depolarization ratio (PDR)) are derived from lidar measurements at 355 nm during the period between 13 and 22 June 2019. The background aerosol content with an aerosol optical thickness (AOT) of 0.10 ± 0.05, corresponding to local–regional conditions influenced by anthropogenic pollution, has been characterized over the entirety of Lake Annecy thanks to the mobile ultralight payload. The aerosol optical properties are shown to be particularly variable over time in the atmospheric column, with mean LRs (PDRs) varying between 40 ± 8 and 115 ± 15 sr (2 ± 1 and 35 ± 2%). Those conditions can be disturbed by air masses that have recirculated over the valley, as well as by contributions from neighboring valleys. We have observed an important disruption in the atmospheric aerosol profiles by the arrival of an exceptionally dry air mass (RH ~ 30%), containing aerosols identified as coming from the Great Western Erg (AOT ~ 0.5, LR = 65 ± 10 sr, PDR = 20–35%) in the Sahara. These desert dust particles are shown to influence the entire atmospheric column in the Annecy valley. Such an experimental approach, coupling upward and downward lidar and spaceborne observation/Lagrangian modelling, was shown to be of significant interest for the long-term monitoring of the evolution of aerosol loads over deep valleys. It allows a better understanding of the influence of dust storms in the presence of severe convective weather processes. [ABSTRACT FROM AUTHOR]

Aerosol Optical Depth (AOD) and the Ångström Exponent (AE) have been calculated in the near infrared (NIR) and short-wave infrared (SWIR) spectral regions over a period of one year (May 2019–May 2020) at the high-mountain Izaña Observatory (IZO) from Fourier Transform Infrared (FTIR) solar spectra. The high-resolution FTIR measurements were carried out coincidentally with Cimel CE318-T photometric observations in the framework of the Aerosol Robotic Network (AERONET). A spectral FTIR AOD was generated using two different approaches: by means of the selection of seven narrow FTIR micro-windows (centred at 1020.90, 1238.25, 1558.25, 1636.00, 2133.40, 2192.00, and 2314.20 nm) with negligible atmospheric gaseous absorption, and by using the CE318-AERONET's response function in the near-coincident bands (1020 nm and 1640 nm) to degrade the high-resolution FTIR spectra. The FTIR system was absolutely calibrated by means of a continuous Langley–Plot analysis over the 1-year period. An important temporal drift of the calibration constant was observed as a result of the environmental exposure of the FTIR's external optical mirrors (linear degradation rate up to 1.75% month − 1 ). The cross-validation of AERONET-FTIR databases documents an excellent agreement between both AOD products, with mean AOD differences below 0.004 and root-mean-squared errors below 0.006. A rather similar agreement was also found between AERONET and FTIR convolved bands, corroborating the suitability of low-resolution sunphotometers to retrieve high-quality AOD data in the NIR and SWIR domains. In addition, these results demonstrate that the methodology developed here is suitable to be applied to other FTIR spectrometers, such as portable and low-resolution FTIR instruments with a potentially higher spatial coverage. The spectral AOD dependence for the seven FTIR micro-windows have been also examined, observing a spectrally flat AOD behaviour for mineral dust particles (the typical atmospheric aerosols presented at IZO). A mean AE value of 0.53 ± 0.08 for pure mineral dust in the 1020–2314 nm spectral range was retrieved in this paper. A subsequent cross-validation with the MOPSMAP (Modeled optical properties of ensembles of aerosol particles) package has ensured the reliability of the FTIR dataset, with AE values between 0.36 to 0.60 for a typical mineral dust content at IZO of 100 cm − 3 and water-soluble particle (WASO) content ranging from 600 to 6000 cm − 3 . The new database generated in this study is believed to be the first long-term time series (1-year) of aerosol properties generated consistently in the NIR and SWIR ranges from ground-based FTIR spectrometry. As a consequence, the results presented here provide a very promising tool for the validation and subsequent improvement of satellite aerosol products as well as enhance the sensitivity to large particles of the existing databases, required to improve the estimation of the aerosols' radiative effect on climate. [ABSTRACT FROM AUTHOR]

Monitoring vegetation changes over time is very important in dry areas such as Iran, given its pronounced drought-prone agricultural system. Vegetation indices derived from remotely sensed satellite imageries are successfully used to monitor vegetation changes at various scales. Atmospheric dust as well as airborne particles, particularly gases and clouds, significantly affect the reflection of energy from the surface, especially in visible, short and infrared wavelengths. This results in imageries with missing data (gaps) and outliers while vegetation change analysis requires integrated and complete time series data. This study investigated the performance of HANTS (Harmonic ANalysis of Time Series) algorithm and (M)-SSA ((Multi-channel) Singular Spectrum Analysis) algorithm in reconstruction of wide-gap of missing data. The time series of Normalized Difference Vegetation Index (NDVI) retrieved from Landsat TM in combination with 250m MODIS NDVI time image products are used to simulate and find periodic components of the NDVI time series from 1986 to 2000 and from 2000 to 2015, respectively. This paper presents the evaluation of the performance of gap filling capability of HANTS and M-SSA by filling artificially created gaps in data using Landsat and MODIS data. The results showed that the RMSEs (Root Mean Square Errors) between the original and reconstructed data in HANTS and M-SSA algorithms were 0.027 and 0.023 NDVI value, respectively. Further, RMSEs among 15 NDVI images extracted from the time series artificially and reconstructed by HANTS and M-SSA algorithms were 0.030 and 0.025 NDVI value, respectively. RMSEs of the original and reconstructed data in HANTS and M-SSA algorithms were 0.10 and 0.04 for time series 6, respectively. The findings of this study present a favorable option for solving the missing data challenge in NDVI time series. [ABSTRACT FROM AUTHOR]

Close-range photogrammetry is a powerful and widely used technique for 3D reconstruction of archaeological environments, specifically when a high-level detail is required. This paper presents an innovative low-cost system that allows high quality and detailed reconstructions of indoor complex scenarios with unfavorable lighting conditions by means of close-range nadir and oblique images as an alternative to drone acquisitions for those places where the use of drones is limited or discouraged: (i) indoor scenarios in which both loss of GNSS signal and need of long exposure times occur, (ii) scenarios with risk of raising dust in suspension due to the proximity to the ground and (iii) complex scenarios with variability in the presence of nooks and vertical elements of different heights. The low-altitude aerial view reached with this system allows high-quality 3D documentation of complex scenarios helped by its ergonomic design, self-stability, lightness, and flexibility of handling. In addition, its interchangeable and remote-control support allows to board different sensors and perform both acquisitions that follow the ideal photogrammetric epipolar geometry but also acquisitions with geometry variations that favor a more complete and reliable reconstruction by avoiding occlusions. This versatile pole photogrammetry system has been successfully used to 3D reconstruct and document the "Cueva Pintada" archaeological site located in Gran Canaria (Spain), of approximately 5400 m2 with a Canon EOS 5D MARK II SLR digital camera. As final products: (i) a great quality photorealistic 3D model of 1.47 mm resolution and ±8.4 mm accuracy, (ii) detailed orthophotos of the main assets of the archaeological remains and (iii) a visor 3D with associated information on the structures, materials and plans of the site were obtained. [ABSTRACT FROM AUTHOR]

Aerosol robotic network (AERONET) data from Dongsha Island (20.699N, 116.729E) and Taiping Island (35.90N, 3.03W) over the South China Sea (SCS) from January 2018 to December 2020 were used to analyze and discuss the temporal evolution properties of aerosols in the South China Sea. Surrounding AERONET stations (Hong Kong, NSPO, Nha Trang and Singapore) were also used to analyze regional characteristics. High aerosol loads over Dongsha were strongly associated with the anthropogenic fine particle transport from the southeastern coast of China and occasional advection of desert dust from Mongolian areas. The high fine aerosol loading in Taiping originates from the region between Singapore and Indonesia. Compared with other marine islands in the world, SCS was not a pure marine aerosol environment and was affected by terrestrial aerosols. In the Taiping area, aerosol optical depth τ (500 nm) was 0.17 ± 0.13 and the average Ångström exponent α (440–870 nm) was 0.96 ± 0.36. However, that of Dongsha shows the larger values of τ (0.26 ± 0.21) and α (1.1 ± 0.38), indicating that there are large fluctuations in aerosol concentration and size. Aerosol loads in different regions of the SCS due to uneven socioeconomic and complex meteorological systems, such as those of the coastal cities of China, Singapore, and the region between Singapore and Indonesia, contribute to the high optical depth. The special meteorological regime and aerosol source mechanism in the SCS leads to the obvious seasonal cycle of aerosol optical depth and Ångström index. Moreover, the loading variations of aerosols on Dongsha Island and Taiping Island were highly consistent with those of coastal cities around them, suggesting the significant effect of the aerosol in the SCS by the surrounding coastal cities, although the aerosol optical depth in these two places was much lower than that in the surrounding cities. [ABSTRACT FROM AUTHOR]

The climate effect and environmental pollution caused by dust discharged into the atmosphere have attracted much attention. However, the driving factors of dust emissions have not been studied thoroughly. Here, spatiotemporal variations in dust emissions and the relationship between dust emissions and large-scale atmospheric circulation in East Asia from 2000 to 2021 were investigated using Modern-Era Retrospective Analysis for Research and Applications version 2, Cloud-Aerosol Lidar Pathfinder Satellite Observations, ERA5 reanalysis data, and climate indices. Results showed that the Taklimakan Desert in the Tarim Basin, the Gurbantonggut Desert in the Junggar Basin, the Turpan Basin, and the Gobi Desert in western Inner Mongolia and southern Mongolia are the main sources of dust emissions in East Asia. The period of strong dust emissions is from March to May, and emissions to the atmosphere were mainly distributed at 0–4 km in the troposphere. In the eastern and southwestern Tarim Basin, northern Junggar Basin, and parts of the Gobi Desert in southern Mongolia, dust emissions have significantly increased over the past 22 years, whereas in the southwestern Tibetan Plateau, southwestern Inner Mongolia, and a small part of the northern Mongolian Gobi Desert there was a significant decreasing trend. The winter North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were significantly negatively correlated with East Asian dust emissions the following spring. The various phases of the AO/NAO coupling have clear different effects on East Asian dust emissions in the spring. When the AO/NAO coupling was negative (positive), the East Asian trough and Siberian High were strengthened (weakened), the frequency of cold air activity increased (weakened), 800 hPa wind speed strengthened (weakened), and East Asian emissions increased (decreased). In AO−/NAO+ years, the Asian polar vortex was stronger to the south and the East Asian trough was stronger to the west. The Lake Baikal trough was in the deepening phase, which caused more polar cold air to move into East Asia, aggravating the intensity of dust activity. In the AO+/NAO− years, the Siberian High and East Asian trough weakened, which was unfavorable to the southward movement of cold air from Siberia. Therefore, the frequency of windy weather in East Asia decreased, partly weakening dust emissions. However, a positive geopotential anomaly in northeast China and a negative geopotential anomaly in South Asia triggered an anomalous enhancement in easterly wind in the tropospheric area over northwest China. Strengthening of the Balkhash trough provides favorable conditions for gale weather in northwest China. The frequency of gale weather increased, and dust emissions were enhanced in northwest China. [ABSTRACT FROM AUTHOR]

On 19 September 2021, a volcanic eruption began on the island of La Palma (Canary Islands, Spain). The eruption has allowed the assessment of an unprecedented multidisciplinary study on the effects of the volcanic plume. This work presents the estimation of the spectral direct radiative forcing (Δ F) and efficiency (Δ F E f f ) from solar radiation measurements at the Izaña Observatory (IZO) located on the island of Tenerife (∼140 km from the volcano). During the eruption, the IZO was affected by different types of aerosols: volcanic, Saharan mineral dust, and a mixture of volcanic and dust aerosols. Three case studies were identified using ground-based (lidar) data, satellite-based (Sentinel-5P Tropospheric Monitoring Instrument, TROPOMI) data, reanalysis data (Modern-Era Retrospective Analysis for Research and Applications, version 2, MERRA-2), and backward trajectories (Flexible Trajectories, FLEXTRA), and subsequently characterised in terms of optical and micro-physical properties using ground-based sun-photometry measurements. Despite the Δ F of the volcanic aerosols being greater than that of the dust events (associated with the larger aerosol load present), the Δ F E f f was found to be lower. The spectral Δ F E f f values at 440 nm ranged between −1.9 and −2.6 Wm − 2 nm − 1 AOD − 1 for the mineral dust and mixed volcanic and dust particles, and between −1.6 and −3.3 Wm − 2 nm − 1 AOD − 1 for the volcanic aerosols, considering solar zenith angles between 30 ∘ and 70 ∘ , respectively. [ABSTRACT FROM AUTHOR]

Recently, dust has created many problems, including negative effects on health, and environmental and economic costs, for people who live both near to and far from sources of dust. The aim of this study is to evaluate and quantify the impact of dust sources located inside Saudi Arabia on the physical growth and vegetation status of cities. In order to do so, satellite data sets, simulated surface data, and soil data for Saudi Arabia from 2000 to 2021 were used. In the first step, a dust sources map of the study area was generated using multi-criteria decision analysis. Land surface temperature (LST), vegetation cover, soil moisture, precipitation, air humidity, wind speed, and soil erodibility factors were considered as effective criteria in identifying dust sources. In the second step, built-up land and vegetation status maps of major cities located at different distances from dust sources were generated for different years based on spectral indicators. Then, the spatiaotemporal change of built-up land and vegetation status of the study area and major cities were extracted. Finally, impacts of major dust sources on urban physical growth and vegetation were quantified. The importance degrees of soil erodibility, wind speed, soil moisture, vegetation cover, LST, air humidity, and precipitation to identify dust sources were 0.22, 0.20, 0.16, 0.15, 0.14, 0.07, and 0.05, respectively. Thirteen major dust sources (with at least 8 years of repetition) were identified in the study area based on the overlap of the effective criteria. The identified major dust sources had about 300 days with Aerosol Optical Depth (AOD) values greater than 0.85, which indicates that these dust sources are active. The location of the nine major dust sources identified in this study corresponds to the location of the dust sources identified in previous studies. The physical growth rates of cities located <400 km or >400 km from a major dust source (DMDS) are 46.2% and 95.4%, respectively. The reduction rates of average annual normalized difference vegetation index (NDVI) in these sub-regions are 0.006 and 0.002, respectively. The reduction rate of the intensity of vegetation cover in the sub-region close to dust sources is three times higher than that of the sub-region farther from dust sources. The coefficients of determination (R2) between the DMDS and urban growth rate and the NDVI change rate are 0.52 and 0.73, respectively, which indicates that dust sources have a significant impact on the physical growth of cities and their vegetation status. [ABSTRACT FROM AUTHOR]

The AERONET (Aerosol Robotic Network) global network provides estimations of broadband solar radiative fluxes at the surface and at the TOA (Top-Of-the-Atmosphere). This paper reports on the validation of AERONET flux estimations at the TOA with the CERES (Clouds and the Earth's Radiant Energy System) instrument. The validation was made at eight AERONET sites worldwide with at least seven years of Level 2.0 and Version 3 data and representatives of mineral dust, biomass burning, background continental, and urban-industrial aerosol regimes. To co-locate in time and space the AERONET and CERES fluxes, several criteria based on time and distance differences and cloud coverage were defined. When the strictest criterion was applied to all sites, the linear relationship between the observed and estimated fluxes (y = 1.04x – 3.67 Wm−2) was very close to the 1:1 ideal line. The correlation coefficient was 0.96 and nearly all points were contained in the ±15% region around the 1:1 line. The average flux difference was –2.52 Wm−2 (−0.84% in relative terms). AERONET overestimations were observed at two sites and were correlated with large aerosol optical depth (AOD) (>0.2) Underestimations were observed at one desert site and were correlated with large surface albedos (>0.2). [ABSTRACT FROM AUTHOR]

Sand and dust storm events (SDEs), which result from strong surface winds in arid and semi-arid areas, exhibiting loose dry soil surfaces are detrimental to human health, agricultural land, infrastructure, and transport. The accurate detection of near-surface dust is crucial for quantifying the spatial and temporal occurrence of SDEs globally. The Arabian Peninsula is an important source region for global dust due to the presence of extensive deserts. This paper evaluates the suitability of five different MODIS-based methods for detecting airborne dust over the Arabian Peninsula: (a) Normalized Difference Dust Index (NDDI); (b) Brightness Temperature Difference (BTD) (31–32); (c) BTD (20–31); (d) Middle East Dust Index (MEDI) and (e) Reflective Solar Band (RSB). We derive detection thresholds for each index by comparing observed values for 'dust-present' versus 'dust-free' conditions, taking into account various land cover settings and analyzing associated temporal trends. Our results suggest that the BTD (31–32) method and the RSB index are the most suitable indices for detecting dust storms over different land-cover types across the Arabian Peninsula. The NDDI and BTD (20–31) methods have limitations in identifying dust over multiple land-cover types. Furthermore, the MEDI has been found to be unsuitable for detecting dust in the study area across all land-cover types. [ABSTRACT FROM AUTHOR]

Sand and dust storms (SDSs) are common environmental hazards in spring in Asian continent and have significant impacts on human health, weather, and climate. While many technologies have been developed to monitor SDSs, this study investigates the spectral characteristics of SDSs in satellite hyperspectral infrared observations and propose a new methodology to monitor the storms. An SDS emission and scattering index (SESI) is based on the differential responses of infrared CO2 shortwave and longwave IR bands to the scattering and emission of sand and dust particles. For a severe dust storm process during 14–17 March 2021, the SESI calculated by the Cross-track Infrared Sounder (CrIS) observations shows very negative values in the dusty region and is consistent with the spatial distribution of dust identified from the true-color RGB imagery and the dust RGB imagery of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NOAA-20 Satellite. The use of the SESI index in the near-surface layer allows for monitoring of the dust storm process and enables an effective classification between surface variations and dust weather events. [ABSTRACT FROM AUTHOR]

Rapid urbanization has produced a huge amount of construction waste. The operations and consequences of construction and demolition can lead to windblown dust problems, profoundly affecting the living environment of residents. Fortunately, dust-proof nets have been used in construction sites to reduce and prevent pollution by fine particles such as dust, so it is important to monitor and evaluate their efficacy. In this study, Earth observation techniques were used for the extraction and monitoring of solid waste and dust-proof nets. In order to fully perceive the validity and necessity of dust-proof nets for urban air health, we conducted a case study in Zhengzhou, China. We explored the potential of multispectral remote sensing available for monitoring urban construction waste and proposed a multi-layer classification method to identify construction waste and dust-proof nets based on Landsat-8 OLI and Sentinel-2 MSI data, with an average identification accuracy and Kappa coefficient of 96.27% and 0.93 for construction waste in the study area from 2015 to 2020, respectively. In addition, our study revealed the driving factors and impact of temporal variations in regional construction waste areas and dust-proof nets coverage. The results indicate the classification can track municipal solid waste management and changes in air pollutant concentrations and is useful for achieving SDG 11.6 (reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management). This study has the potential to monitor construction waste and dust-proof nets, paving the way for better urban environmental governance and surveillance actions in the future, especially involving big data. [ABSTRACT FROM AUTHOR]

The long-range transport of desert dust over the area of the temperate climate zone is associated with the influx of hot air masses due to the location of the sources of this aerosol in the tropical climate zone. Between 24–26 February 2021, such an aerosol outbreak took place and reached Central Europe. The mean temperature of +11.7 °C was recorded during the event. A comparison of this value to the 20-year (2000–2020) average February temperature for Warsaw (−0.2 °C) indicates the uniqueness of the meteorological conditions. It was the first wintertime inflow of Saharan dust over Warsaw, the presence of which was confirmed by lidar and sun-photometer measurements. The properties of the desert dust layers were obtained; the mean values of the particle depolarization for the fully developed mineral dust layer were 13 ± 3% and 22 ± 4% for 355 and 532 nm, respectively. The aerosol optical thickness was high with average values >0.36 for all wavelengths smaller than 500 nm. The three-modal, aerosol size distribution was dominated by coarse-mode particles, with a visible contribution of accumulation-mode particles. It suggests the possible presence of other aerosol types. [ABSTRACT FROM AUTHOR]

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD550, fine mode AOD (FAOD550; also known as FM AOD in the literature), coarse mode AOD (CAOD550), and fine mode fraction (η550) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD550. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD550 values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD550 are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD550 and FAOD550 but perform better in characterizing the CAOD550. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD550 and FAOD550 high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s−1, the C4C and MODIS AOD550s also overestimate CAOD550 and FAOD550, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely even larger than what was diagnosed here. We conclude with a discussion on how MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research. [ABSTRACT FROM AUTHOR]

The vertical structure of dust properties in desert sources is crucial for evaluating their long-range transportation and radiative forcing. To investigate vertical profiles of dust optical properties in the Taklimakan Desert, we conducted ground-based polarization Raman lidar measurements in Tazhong (83.39°E, 38.58°N, 1103 m above sea level), located at the center of the Taklimakan Desert in the summer of 2019. The lidar system developed by Lanzhou University for continuous network observation is capable of measuring polarization at 532 and 355 nm and detecting Raman signals at 387, 407, and 607 nm. The results indicate that dust aerosols in the central Taklimakan Desert were regularly lifted over 6 km during the summer with a mass concentration of 400–1000 µg m−3, while the majority of the dust remained restricted within 2 km. Moreover, the height of the boundary layer can reach 5–6 km in the afternoon under the strong convention. Above 3 km, dust is composed of finer particles with an effective radius (Reff.) less than 3 μm and a Ångström exponent (AE) related to the extinction coefficient (AEE)532,355 greater than 4; below 3 km, however, dust is dominated by coarser particles. In addition, the particle depolarization ratios (PDR) of Taklimakan dust are 0.32 ± 0.06 at 532 nm and 0.27 ± 0.04 at 355 nm, while the lidar ratios (LRs) are 49 ± 19 sr at 532 nm and 43 ± 12 sr at 355 nm. This study firstly provides information on dust vertical structure and its optical properties in the center of the desert, which may aid in further evaluating their associated impacts on the climate and ecosystem. [ABSTRACT FROM AUTHOR]

Drying lakes have become a new source of dust, causing severe problems in surrounding areas. From 2000 to 2017, a statistical study was conducted on Lake Urmia in Iran in the Middle East. The results indicated a significant increase in the annual number of dusty days in stations around the lake and the mean annual aerosol optical depth (AOD) at 550 nm. The sharp decrease in annual snowfall rate over the Lake Urmia area since 2007 has been linked to the lake's decreasing water level and drying. During a dust storm event from 27 October to 31 October 2017, a local dust storm originated from Lake Urmia before another large-scale dust storm originated from the An-Nafud desert. According to MODIS true-color images, dust particles were lifted from Lake Urmia and transported eastward to the Caspian Sea and the HYSPLIT model. The comparison of the four models under the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) revealed that the models overestimated surface dust concentrations compared to ground-based PM10 measurements. Nevertheless, the NOAA/WRF-Chem and DREAMABOL models simulated higher dust concentrations during the dust period. More emphasis should be placed on the development of dust models for SDS-WAS models in Lake Urmia. [ABSTRACT FROM AUTHOR]

Dust aerosols persistently affect nearly all landscapes worldwide, and the saltation activity caused by dusty weather (e.g., dust days) releases considerable amounts of aerosol into the atmosphere. Nevertheless, dust-induced saltation activity may also occur on non-dust days. To date, few studies have investigated the saltation activity characteristics on non-dust days. Moreover, the contribution of non-dust days to the total saltation activity remains ambiguous. This study comprehensively investigates the characteristics of saltation activity on non-dust days. Specifically, we analyze the influence of the saltation activity of non-dust days on dust aerosols by utilizing saltation, atmospheric, soil, dust aerosol (i.e., PM10 and aerosol optical depth), and weather record data obtained from the Taklimakan Desert, China, between 2008 and 2010. Our results show that lower temperature, vapor pressure, and soil moisture on non-dust days reduces the saltation threshold velocity (5.9 m/s) more compared to on dust days (6.5 m/s). Furthermore, regarding wind speed, relatively strong monthly saltation activity occurs from March to August, and daily saltation activity occurs from 9:00 to 16:00. Although non-dust days only contribute 18.5% and 7.7% to saltation time and saltation count, respectively, both significantly influence the dust aerosols. Therefore, the effect of saltation activity on non-dust days cannot be undervalued, particularly while performing dust aerosol studies. [ABSTRACT FROM AUTHOR]