Aerosol Types Research Articles

Temporal distributions of aerosols over the Horn of Africa–Ethiopia using MODIS satellite data: Part 01

There are large temporal variations in the optical properties and types of aerosols. These are due to the effects of environmental and meteorological conditions, industrial and agricultural influences, and other human influences and natural factors in each ecological functional area. Aerosol optical depth AOD and Ångström exponent AE parameters were extracted from the Moderate Resolution Imaging Spectroradiometer MODIS satellite with a 3 km resolution of MOD04_3K and MYD04_3K. The study covers sixteen selected stations in Horn Africa–Ethiopia with neighboring Eritrea, Djibouti, and South Sudan countries clustered into four regions for the periods of 2001–2022 to obtain detailed information on the temporal behaviors and classification of aerosols in each season. The results show that the temporal variability of AOD and AE values is large, with values ranging from 0.00 to 2.10 and 0.67 to 1.23, with minimum values most likely between December 16 and January 07, and maximum values between June 22 and July 24 for both Terra and Aqua in the southeast and northeast clusters, respectively. The lowest AOD and AE values were most common in the Belg (during September–November) and sometimes in Bega (during December–February), while the highest were in the Kiremt season (during June–August). The minimum values were observed at the Kebri Dahar site, and the maximum were at the Erta Ale site, which belongs to Ethiopia. Appropriate AOD and AE thresholds were used to classify the aerosol types into marine (MR), dust (DS), biomass burning (BB), desert dust (DD), urban (UR), and the residual cases were considered mixture (MX) types. The study concludes that marine aerosols were the most abundant at 47.71%, followed by urban aerosols at 28.29%, while desert dusts, enriched at 14.65%, accounted for the third place with free of dust particles. The Mann–Kendall (MK) statistical trend test was applied to the annual time series in all clustered regions and shows an almost positive increasing variability with a slight decrease in the forward series and vice–versa.

Global aerosol models considering their spatial heterogeneities based on AERONET measurements

The imprecision inherent in aerosol models poses a significant challenge in satellite- and surface- based aerosol retrieval. The correct classification of global aerosol types and understanding of their spatial heterogeneity are prerequisites for accurately deriving aerosol optical and microphysical properties and assessing their impacts on climate, air quality, and human health. In this study, a deep clustering algorithm is developed and employed to classify global aerosol types by using >160,000 records of AERONET measurements at 411 sites during 2000–2020. The proposed algorithm utilizes deep learning techniques to optimize the feature space of input variables, thereby improving the distinguishability among various aerosol types. This algorithm outperforms the commonly used K-means method with 77.4% of AERONET sites experiencing increased explained variance. Based on their unique properties (e.g., single scattering albedo, complex refractive index and dust ratio, etc.) and geographic distribution, global aerosols are classified into six types: mineral dust, smoke, two urban aerosols with different particle sizes, and two mixtures with different dominant components. The spatial heterogeneity of aerosol optical/microphysical properties is distinctly presented in our clustering results. Through the subdivision of the global domain into 11 sub-regions, a comprehensive elucidation has been undertaken to delineate the variances in volume size distribution, absorption, and scattering characteristics exhibited among disparate aerosol types, as well as within a same aerosol category. These new understandings of aerosol models and their spatial heterogeneities in this study will be highly helpful to update or optimize aerosol retrieval algorithms in the future.

Bridging the Gap: Establishing Spatial Correlations and Type Conversion Relationships among Different Aerosol Idetification Methods

Effective identification of aerosol type is the basis of accurate quantification of aerosol-climate and aerosol-environment interactions. However, there are different aerosol category settings and identifying parameter selections among different aerosol identification methods, which causes incoherence in data comparisons and uncertainty in quantifying thier climate and environment effects. To bridge the gap, this study establishes spatial correlations and aerosol type conversion relationships among four commonly-used aerosol identification methods, which includes AOD-AE, AE-SSA, FMF-SSA, and SAE-AAE. Aerosol optical properties observed at 37 typical AERONET sites are selected as the testbed, including marine, desert dust, clean continent, urban industry, and biomass burning sites. Results show that marine and desert dust aerosols are the most effectively identified types, while urban industry and biomass burning aerosols overlap much in the identification spaces since they contain similar chemical components. Dust and marine aerosol generally have the best agreement among the four identification methods, because desert dust and marine particles have distinctive chemical components from other kinds, thus the category setting from the perspective of emission source, light absorbing ability, or chemical components has less influence on the identification results. Spatial correlation between the four commonly-used aerosol identification methods futher refines the correspondence of aerosol category, light absorption capacity, and chemical components. And we find that uncertain aerosols defined in FMF-SSA are mostly marine aerosols.

An effort to distinguish the effects of cloud cover and aerosols on the decadal variations of surface solar radiation in the Northern Hemisphere

Surface solar radiation (SSR) serves as the primary energy source on Earth. However, a relative lack of research systematically quantifies long-term SSR variations and their driving factors based on complete and reliable baseline data. This paper presents a new assessment of the Northern Hemisphere/regional SSR variations and the influence of total cloud cover (TCC) on these variations, based on the latest reconstructed SSR gridded dataset. We also address multicollinearity among multiple aerosol types and quantify the effects of multiple aerosol/precursors on SSR variability using a partial least squares regression model. The results indicate that TCC is not the predominant driver of longer-term SSR variations, known as ‘dimming’ and ‘brightening’. The variations of NH3 and SO2 primarily drive inter-decadal SSR variations in North America, while the variations of SO2 and NO X mainly influence inter-decadal SSR variations in Europe.

Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy

Abstract. This study focuses on the characterization of aerosol hygroscopicity using remote sensing techniques. We employ a Mie–Raman–fluorescence lidar (Lille Lidar for Atmospheric Study, LILAS), developed at the ATOLL platform, Laboratoire d'Optique Atmosphérique, Lille, France, in combination with the RPG-HATPRO-G5 microwave radiometer to enable continuous aerosol and water vapor monitoring. We identify hygroscopic growth cases when an aerosol layer exhibits an increase in both aerosol backscattering coefficient and relative humidity. By examining the fluorescence backscattering coefficient, which remains unaffected by the presence of water vapor, the potential temperature, and the absolute humidity, we verify the homogeneity of the aerosol layer. Consequently, the change in the backscattering coefficient is solely attributed to water uptake. The Hänel theory is employed to describe the evolution of the backscattering coefficient with relative humidity and introduces a hygroscopic coefficient, γ, which depends on the aerosol type. The particularity of this method revolves around the use of the fluorescence which is employed to take into account and correct the aerosol concentration variations in the layer. Case studies conducted on 29 July and 9 March 2021 examine, respectively, an urban and a smoke aerosol layer. For the urban case, γ is estimated as 0.47 ± 0.03 at 532 nm; as for the smoke case, the estimation of γ is 0.5 ± 0.3. These values align with those reported in the literature for urban and smoke particles. Our findings highlight the efficiency of the Mie–Raman–fluorescence lidar and microwave radiometer synergy in characterizing aerosol hygroscopicity. The results contribute to advance our understanding of atmospheric processes, aerosol–cloud interactions, and climate modeling.

Reply to: “Comment on ‘Stratospheric Aerosol Composition Observed by the Atmospheric Chemistry Experiment Following the 2019 Raikoke Eruption’ by Boone et al.” by Ansmann et al.

AbstractThe question of stratospheric aerosol type following the Raikoke eruption is revisited. Raman lidar measurements suggest the aerosols are predominately smoke, while Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE‐FTS) results indicate the aerosols are predominately sulfate aerosols. The suggested mechanism of smoke particles self‐lofting into the stratosphere is inconsistent with observations in 2020, when more severe Siberian fires failed to invoke a response even vaguely similar to 2019. A side‐by side comparison of the Sarychev and Raikoke eruptions invalidates model calculations that suggest sulfate aerosols should be at levels too low to explain the observed aerosol loading. Structure in infrared absorption spectra provides conclusive evidence of composition, a unique fingerprint for identifying aerosol type. Such information cannot be misinterpreted so long as there is sufficient resolution and spectral coverage. ACE‐FTS infrared aerosol spectra often have an order of magnitude stronger absorption than that of background sulfate aerosols. These spectra can be accurately reproduced by laboratory measured sulfate aerosol spectroscopic information, providing unambiguous identification of the aerosols as sulfate. Visual inspection of thousands of infrared aerosol spectra from the period following the Raikoke eruption indicates the aerosols in the lower stratosphere are predominately sulfate, with no indication of smoke. The lidar study's identification of the aerosols as smoke was based primarily on observed lidar ratios that were more consistent with a material that absorbed significantly at the lidar wavelengths, inconsistent with expectations for sulfate aerosols. However, this could indicate the presence of a substance dissolved in the sulfate aerosols absorbing at those wavelengths rather than smoke particles.

Comment on “Stratospheric Aerosol Composition Observed by the Atmospheric Chemistry Experiment Following the 2019 Raikoke Eruption” by Boone et al.

AbstractBased on satellite observations in the Arctic stratosphere at latitudes from 61° to 66°N in the second half of 2019, Boone et al. (2022, https://doi.org/10.1029/2022jd036600) provide the impression that the aerosol in the upper troposphere and lower stratosphere (UTLS) over the entire Arctic consisted of sulfate aerosol originating from the Raikoke volcanic eruption in the summer of 2019. Here, we show that this was most probably not the case and the aerosol layering conditions were much more complex. By combining the stratospheric aerosol typing results of Boone et al. (2022, https://doi.org/10.1029/2022jd036600) with lidar observations at 85°–86°N of Ohneiser et al. (2021, https://doi.org/10.5194/acp‐21‐15783‐2021) of a dominating wildfire smoke layer in the UTLS height range, we demonstrate that the Arctic UTLS aerosol most likely consisted of Siberian wildfire smoke in the lower part and sulfate aerosol in the upper part of the aerosol layer which extended from 7 to 19 km height and was well observable until May 2020. The smoke‐ and sulfate‐related aerosol optical thickness (AOT) fractions were about 0.7–0.8 and 0.2–0.3, respectively, according to our analysis. The sulfate AOT is in good agreement with model‐based predictions of the Raikoke sulfate AOT.

Simultaneous organic aerosol source apportionment at two Antarctic sites reveals large-scale and ecoregion-specific components

Abstract. Antarctica and the Southern Ocean (SO) are the most pristine areas of the globe and represent ideal places to investigate aerosol–climate interactions in an unperturbed atmosphere. In this study, we present submicrometer aerosol (PM1) source apportionment for two sample sets collected in parallel at the British Antarctic Survey stations of Signy and Halley during the austral summer of 2018–2019. Water-soluble organic matter (WSOM) is a major aerosol component at both sites (37 % and 29 % of water-soluble PM1, on average, at Signy and Halley, respectively). Remarkable differences between pelagic (open-ocean) and sympagic (influenced by sea ice) air mass histories and related aerosol sources are found. The application of factor analysis techniques to series of spectra obtained by means of proton-nuclear magnetic resonance (H-NMR) spectroscopy on the samples allows the identification of five organic aerosol (OA) sources: two primary organic aerosol (POA) types, characterized by sugars, polyols, and degradation products of lipids and associated with open-ocean and sympagic/coastal waters, respectively; two secondary organic aerosol (SOA) types, one enriched in methanesulfonic acid (MSA) and dimethylamine (DMA) and associated with pelagic waters and the other characterized by trimethylamine (TMA) and linked to sympagic environments; and a fifth component of unclear origin, possibly associated with the atmospheric aging of primary emissions. Overall, our results strongly indicate that the emissions from sympagic and pelagic ecosystems affect the variability in the submicrometer aerosol composition in the study area, with atmospheric circulation establishing marked latitudinal gradients only for some of the aerosol components (e.g., the sympagic components) while distributing the others (e.g., pelagic and/or aged components) both in maritime and inner Antarctic regions.

Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types.

It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)440-Angstrom exponent (AE)440-870 method (AA1M), and AOD550-AE490-670 method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.

Using HawkEye Level-2 Satellite Data for Remote Sensing Tasks in the Presence of Dust Aerosol

This paper is the first to examine the operation of the HawkEye satellite in the presence of dust aerosol. The study region is the Black Sea. Dust transport dates were identified using visual inspection of satellite imagery, back-kinematic HYSPLIT trajectory analysis, CALIPSO aerosol stratification and typing maps, and the global forecasting model SILAM. In a comparative analysis of in-situ and satellite measurements of the remote sensing reflectance, an error in the atmospheric correction of HawkEye measurements was found both for a clean atmosphere and in the presence of an absorbing aerosol. It is shown that, on average, the dependence of the atmospheric correction error on wavelength has the form of a power function of the form from λ−3 to λ−9. The largest errors are in the short-wavelength region of the spectrum (412–443 nm) for the dust and dusty marine aerosol domination dates. A comparative analysis of satellite and in situ measurements of the optical characteristics of the atmosphere, namely the AOD and the Ångström parameter, was carried out. It is shown that the aerosol model used by HawkEye underestimates the Angström parameter and, most likely, large errors and outliers in satellite measurements are associated with this.

Quantification of Contributions from Different Dust Sources to the Distribution and the Variation of Spring Dust over the Tibetan Plateau and Corresponding Mechanisms since 2000

Abstract Dust is the predominant type of aerosol over the Tibetan Plateau (TP) due to the existence of surrounding significant dust sources. However, the contributions of different dust sources to the distribution and variation of dust over the TP and corresponding mechanisms are still being explored. By separating emissions from different dust sources in a numerical model, this study detected that dust originating from East Asia, the Middle East, and North Africa are the main contributors to spring dust over the TP, accounting for 42%–68%, 13%–27%, and 9%–25% of the total dust concentration, respectively. East Asian dust primarily affects the dust over the central and northern parts of the TP, whereas Middle Eastern and North African dust mainly contributes to the dust over the western and southern parts of the TP. Additionally, the variation in dust over the TP is related to East Asian and North African dust, which contribute 58% and 35% of the total variation, respectively. The mechanism underlying this association is attributable to the SST over the northern North Atlantic and updrafts over the northern slope of the TP: the increased SST enhances westerlies from North Africa to East Asia and northwesterly winds over the northern slope of the TP and combines with the stronger westerlies to promote the transport of East Asian and North African dust to the TP. Consequently, it is necessary to focus on the impact of multiple dust sources on the dust over the TP.

Optical Properties and Possible Origins of Atmospheric Aerosols over LHAASO in the Eastern Margin of the Tibetan Plateau

The accuracy of cosmic ray observations by the Large High Altitude Air Shower Observatory Wide Field-of-View Cherenkov/Fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples over 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and Ångström Exponent (AE) at 440–870 nm (AE440–870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD is in the order of spring > summer > autumn = winter. The monthly average maximum of AOD440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE440–870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India regions. These results are presented for the first time, providing a detailed analysis of aerosol seasonality and origins, which have not been thoroughly documented before in this region, also enriching the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau.

Volatility and chemical composition of secondary organic aerosol derived from acenaphthylene and acenaphthene under various oxidant conditions

Acenaphthene (ACE) and acenaphthylene (ACY), distinguished by their unique structures, exhibit high reactivity among polycyclic aromatic hydrocarbons (PAHs). Particularly, the rapid ozonolysis of the carbon-carbon double bond in ACY and the swift oxidation of the fused cyclopenta ring in both ACE and ACY by NO3 underscore their distinct atmospheric fate. Through the utilization of a thermo denuder and high-resolution mass spectrometry, the chemical composition and volatility of four types of secondary organic aerosols (SOA) derived from ACE and ACY are investigated. The chemical composition of SOA formed by ACY ozonolysis is characterized by low O: C ratios and high unsaturation, suggesting the retention of aromatic structures. This leads to measured high SOA volatility and is consistent with the low reactivity of O3 with aromatic compounds. In contrast to ozonolysis, the reaction of NO3 with ACY could yield SOA with very low volatility, characterized by abundant dimers and highly oxidized products. Furthermore, the prevalence of compounds with 11 carbon atoms suggests the presence of complex mechanisms in the ACY oxidation process initiated by NO3, where dealkylation reactions and cleavage reactions may be pivotal. The diverse chemical composition and volatility of SOA from ACE and ACY reacting with NO3 radicals highlight the substantial impact of precursor structure on SOA chemical composition, particularly concerning the presence of active carbon-carbon double bonds. The higher O: C ratio of SOA from OH-initiated oxidation of ACE indicates the significant role of OH in the oxidation of PAHs. These findings offer valuable insights into the atmospheric fate of these PAHs, underscoring the necessity for a comprehensive understanding of their degradation processes and the formation of SOA.

Tropospheric sulfate from Cumbre Vieja (La Palma) observed over Cabo Verde contrasted with background conditions: a lidar case study of aerosol extinction, backscatter, depolarization and lidar ratio profiles at 355, 532 and 1064 nm

Abstract. In September 2021, volcanic aerosol (mainly freshly formed sulfate plumes) originating from the eruption of Cumbre Vieja on La Palma, Canary Islands, Spain, crossed Cabo Verde at altitudes below 2 km. On 24 September 2021, an extraordinary large aerosol optical depth (AOD) close to 1 (daily mean at 500 nm) was observed at Mindelo, Cabo Verde. This event provided favorable conditions to obtain lidar-derived profiles of extinction and backscatter coefficients, lidar ratio, and depolarization ratio at 355, 532 and 1064 nm in the sulfate aerosol plume. A novel feature of the lidar system operated at Mindelo is the availability of extinction, lidar ratio and depolarization measurements at 1064 nm in addition to the standard wavelengths of 355 and 532 nm. Having measurements of these parameters at all three wavelengths is a major advantage for the aerosol characterization and in aerosol typing efforts as the lidar ratio and the particle linear depolarization ratio are key parameters for this purpose. In this article, we present the key results of the lidar observations obtained on one specific day, namely on 24 September 2021 at 04:38–05:57 UTC, including the first ever measurements of the particle extinction coefficient, the lidar ratio and the depolarization ratio at 1064 nm for volcanic sulfate, and discuss the findings in terms of aerosol optical properties and mass concentrations by comparison with a reference observation (16 September 2021) representing the typical background conditions before the start of the eruptions. We found an unusual high particle extinction coefficient of 721 ± 51, 549 ± 38 and 178 ± 13 Mm−1, as well as an enhanced lidar ratio of 66.9 ± 10.1, 60.2 ± 9.2 and 30.8 ± 8.7 sr at 355, 532 and 1064 nm, respectively, in the sulfate-dominated planetary boundary layer (PBL). The particle linear depolarization ratio was ≤ 0.9 % at all respective wavelengths. It is the first time that lidar-derived intensive aerosol optical properties could be derived for volcanic sulfate at all three wavelengths, and thus it is a highly valuable data set for global aerosol characterization. The lidar analysis also revealed a sulfate-related AOD of about 0.35 ± 0.03 at 532 nm of the total PBL-related AOD of 0.43. The rest of the AOD contribution was caused by a lofted Saharan dust layer extending from 1.4 to 5 km and leading to a total AOD of 0.79 at 532 nm. Volcanic ash contribution to the observed aerosol plumes could be mostly excluded based on trajectory analysis and the observed optical properties. Peak mass concentration was 178.5 ± 44.6 µg m−3 in the volcanic-influenced and sulfate-dominated polluted PBL, showing the hazardous potential of such sulfate plumes to significantly worsen local air quality even at remote locations.

Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data

Abstract. The properties of aerosols are highly uncertain owing to the complex changes in their composition in different regions. The radiative properties of different aerosol types differ considerably and are vital for studying aerosol regional and/or global climate effects. Traditional aerosol-type identification algorithms, generally based on cluster or empirical analysis methods, are often inaccurate and time-consuming. In response, our study aimed to develop a new aerosol-type classification model using an innovative hybrid algorithm to improve the precision and efficiency of aerosol-type identification. This novel algorithm incorporates an optical database, constructed using the Mie scattering model, and employs a random forest algorithm to classify different aerosol types based on the optical data from the database. The complex refractive index was used as a baseline to assess the performance of our hybrid algorithm against the traditional Gaussian kernel density clustering method for aerosol-type identification. The hybrid algorithm demonstrated impressive consistency rates of 90 %, 85 %, 84 %, 84 %, and 100 % for dust, mixed-coarse (mixed, course-mode aerosol), mixed-fine (mixed, fine-mode aerosol), urban/industrial, and biomass burning aerosols, respectively. Moreover, it achieved remarkable precision, with evaluation metric indexes for micro-precision, micro-recall, micro-F1-score, and accuracy of 95 %, 89 %, 91 %, and 89 %, respectively. Lastly, a global map of aerosol types was generated using the new hybrid algorithm to characterize aerosol types across the five continents. This study, utilizing a novel approach for the classification of aerosol, will help improve the accuracy of aerosol inversion and determine the sources of aerosol pollution.

Annual and Seasonal Variations in Aerosol Optical Characteristics in the Huai River Basin, China from 2007 to 2021

Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) using MODIS, CALIOP observations from 2007 to 2021, and ground-based measurements. A notable finding is a significant decline in the annual mean Aerosol Optical Depth (AOD) across the HRB, with MODIS showing a decrease of approximately 0.023 to 0.027 per year, while CALIOP, which misses thin aerosol layers, recorded a decrease of about 0.016 per year. This downward trend is corroborated by improvements in air quality, as evidenced by PM2.5 measurements and visibility-based aerosol extinction coefficients. Aerosol decreases occurred at all heights, but for aerosols below 800 m, with an annual AOD decrease of 0.011. The study also quantifies the long-term trends of five major aerosol types, identifying Polluted Dust (PD) as the predominant frequency type (46%), which has significantly decreased, contributing to about 68% of the total AOD reduction observed by CALIOP (0.011 per year). Despite this, Dust and Polluted Continental (PC) aerosols persist, with PC showing no clear trend of decrease. Seasonal analysis reveals aerosol peaks in summer, contrary to surface measurements, attributed to variations in the Boundary Layer (BL) depth, affecting aerosol distribution and extinction. Furthermore, the study explores the influence of seasonal wind patterns on aerosol type variation, noting that shifts in wind direction contribute to the observed changes in aerosol types, particularly affecting Dust and PD occurrences. The integration of satellite and ground measurements provides a comprehensive view of regional aerosol properties, highlighting the effectiveness of China’s environmental policies in aerosol reduction. Nonetheless, the persistence of high PD and PC levels underscores the need for continued efforts to reduce both primary and secondary aerosol production to further enhance regional air quality.

Occupational lung diseases from exposure to industrial fibrogenic aerosols of varying degrees of fibrogenicity: occupational risk assessment, features of immunopathogenesis, prediction

The purpose of the study is to assess occupational risk and study the characteristics of immunopathogenesis in occupational lung diseases from exposure to industrial aerosols. Material and research methods. The study included 304 people with over 10 years of work experience under conditions of exposure to high concentrations of industrial fi brogenic aerosols (above the permissible concentration), who underwent an in-depth periodic medical examination at the regional center of occupational pathology Samara City Hospital No. 5 with an assessment of the relative risk (RR), its etiologic fraction (EF), and odds ratio (OR) of the development of occupational respiratory diseases. The comparison group included 120 people. To assess the cytokine profile indices in occupational lung diseases (various degrees of severity of dust-induced occupational diseases, silicosis, and pneumoconiosis from exposure to highly dispersed welding aerosols), 161 people with occupational lung diseases and 60 people in the control group were examined. Levels of immunoglobulins A, M, and G in blood serum, hemolytic activity of complement, and the level of myeloperoxidase were determined using standard reactions. Determination of the levels of total IgE, fibronectin, cytokines IL-1α, IL-1β, IL-4, IL-8, IFNγ, and TNFα, growth factors FGF-2, VEGF in blood serum was carried out by enzyme -linked immunosorbent assay. Results. The occupational risk of developing dust lung diseases from exposure to various types of fibrogenic industrial aerosols, as well as the features of the course of occupational lung diseases have been determined. The identified features of the immu nological profile allow establishing the features of the occurrence, course, and progres sion of occupational lung diseases and recommending changes to the National List of Occupational Diseases. Conclusions. Determining occupational risk and immunological profile allows not only improving the quality of early diagnosis, but optimizing primary and secondary prevention strategies for this pathology, predicting the course of the disease, and reducing the number of disabling forms.

Improvements on Gaussian mixture model and its application in identifying aerosol types in two major cities in the Yangtze River Delta, China

Accurately identifying the authentic local aerosol types is one of the fundamental tasks in studying aerosol radiative effects and model assessment. In this paper, improvements were made to the traditional Gaussian Mixture Model, leading to the following results: 1) This study introduces several improvements to the traditional Gaussian Mixture Model (GMM), referred to as M-GMMs. These improvements include the incorporation of multivariate kurtosis coefficients, Mahalanobis distance instead of Euclidean distance, and weights of variables. The M-GMMs overcome the issues related to dimensional units and correlations among multiple parameters, thereby enhancing the estimation of the covariance matrix. 2) The proposed M-GMMs model was evaluated for its clustering performance using machine-generated data with known classifications and real iris flower data. The results demonstrated that the classification performance of M-GMMs was superior to other models. Furthermore, compared to the slightly less effective K-means algorithm (which requires manual definition of the number of aerosol types), the M-GMMs model was able to automatically iterate and produce consistent classification results based on similar characteristics. 3) There is still a significant disparity between the characteristics of real stations and typical aerosols. Directly evaluating local aerosols using the characteristics of typical aerosols results in substantial errors. However, the M-GMMs model can effectively reflect the authentic aerosol characteristics at the local level. 4) The M-GMMs model was utilized to perform cluster analysis on the Xuzhou and Nanjing stations of AERONET. This analysis yielded quantitative proportions, temporal distribution characteristics, and spectral distribution features of aerosol types in the two regions. The improved M-GMMs model presented in this paper enables more accurate and continuous characterization of aerosol type variations. Its findings hold significant theoretical and practical value in reassessing aerosol radiative effects.

Global horizontal irradiance prediction model for multi-site fusion under different aerosol types

Accurate prediction of global horizontal irradiance (GHI) is crucial for anticipating the volatility of solar power output. Under clear-sky conditions, aerosols play a significant role in influencing GHI, with different types of aerosols exhibiting distinct radiation effects. In this study, we employed the Planck mean aerosol optical depth (AOD) —Informer model to forecast future GHI, utilizing historical data of AOD, meteorological parameters, and GHI as input variables. Two data-fusion schemes were proposed, and the calculation results indicate that Scheme 1, organized in the order of Xianghe—Beijing—Shangdianzi (XBS) based on the day as a unit, demonstrates superior prediction performance. Additionally, the site information was blurred, allowing for the flexible selection of input and output lengths. The calculation results remained stable and reliable, suggesting that the inclusion of fuzzy site information does not degrade the prediction effect. Building upon this, we categorized aerosols into three types based on their time span and data volume. GHI predictions for different aerosol types revealed that the mean square error (0.145) for marine aerosols were significantly lower than those for the other types. The GHI predictions for continental aerosols were closest to the true values.

Local and Regional Diurnal Variability of Aerosol Properties Retrieved by DSCOVR/EPIC UV Algorithm

AbstractThe hour‐to‐hour variability of 388 nm aerosol optical depth (AOD) and single scattering albedo (SSA) derived from near UV observations by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory has been evaluated at multiple locations around the world. AOD retrievals by the EPIC near UV algorithm (EPICAERUV) have been compared to ground based AOD measurements at 16 Aerosol Robotic Network (AERONET) stations representative of the most commonly observed aerosol types over geographic regions in three continents. Obtained results show that, in general, the EPICAERUV algorithm reproduces closely the hour‐to‐hour AOD variability reported by AERONET ground‐truth observations. Although most sites in the analysis show high correlation between the AOD hourly measurements by the ground‐based and space‐borne measuring techniques. Best algorithm performance is observed in the presence of carbonaceous and desert dust aerosols. The diurnal cycle of the retrieved SSA product was also analyzed. Although, a direct comparison of hourly EPICAERUV retrievals to equivalent ground‐based observations was not possible, the satellite result shows that diurnal SSA variability as large as 0.05 can be observed mostly associated with carbonaceous aerosols. EPICAERUV observed diurnal cycle of retrieved AOD on a regional basis was examined for the unusually active seasons of aerosol production of Saharan desert dust aerosols in 2020, and during the 2023 Canadian wildfires. Results presented in this study confirm the EPIC near UV aerosol product is well suited for observing diurnal variability of aerosols and, therefore, it is an important resource for climate and air quality studies.