Aerosol Types Research Articles

Surface Solar Radiation Compositions Observed from Himawari-8/9 and Fengyun-4 Series

Abstract Surface downward solar radiation compositions (SSRC), including photosynthetically active radiation (PAR), ultraviolet-A (UVA), ultraviolet-B (UVB), and shortwave radiation (SWR), with high spatial–temporal resolutions and precision are essential for applications including solar power, vegetation photosynthesis, and environmental health. In this study, an optimal algorithm was developed to calculate SSRC, including their direct and diffuse components. Key features of the algorithm include combining the radiative transfer model with machine learning techniques, including full consideration of the effects of aerosol types, cloud phases, and gas components. A near-real-time monitoring system was developed based on this algorithm, with SSRC products generated from Himawari-8/9 and Fengyun-4 series data. Validation with ground-based data shows that the accuracy of the SWR and PAR compositions (daily mean RMSEs of 19.7 and 9.2 W m−2, respectively) are significantly better than those of state-of-the-art products from CERES, ERA5, and GLASS. The accuracy of UVA and UVB measurements is comparable with CERES. Characteristics of aerosols, clouds, gases, and their impacts on SSRC are investigated before, during, and post COVID-19; in particular, significant SSRC variations due to the reduction of aerosols and increase of ozone are identified in the Chinese central and eastern areas during that period. The spatial–temporal resolution of data products [up to 0.05° (10 min)−1 for the full-disk region] is one of the most important advantages. Data for the East Asia–Pacific region during 2016–20 is available from the CARE home page (www.slrss.cn/care/sp/pc/).

Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean.

The atmosphere over the ocean is an important research field that involves multiple aspects such as climate change, atmospheric pollution, weather forecasting, and marine ecosystems. It is of great significance for global sustainable development. Satellites provide a wide range of measurements of marine aerosol optical properties and are very important to the study of aerosol characteristics over the ocean. In this study, aerosol optical depth (AOD) data from seventeen AERONET (Aerosol Robotic Network) stations were used as benchmark data to comprehensively evaluate the data accuracy of six aerosol optical thickness products from 2013 to 2020, including MODIS (Moderate-resolution Imaging Spectrometer), VIIRS (Visible Infrared Imaging Radiometer Suite), MISR (Multi-Angle Imaging Spectrometer), OMAERO (OMI/Aura Multi-wavelength algorithm), OMAERUV (OMI/Aura Near UV algorithm), and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) in the East Asian Ocean. In the East Asia Sea, VIIRS AOD products generally have a higher correlation coefficient (R), expected error within ratio (EE within), lower root mean square error (RMSE), and median bias (MB) than MODIS AOD products. The retrieval accuracy of AOD data from VIIRS is the highest in spring. MISR showed a higher EE than other products in the East Asian Ocean but also exhibited systematic underestimation. In most cases, the OMAERUV AOD product data are of better quality than OMAERO, and OMAERO overestimates AOD throughout the year. The CALIPSO AOD product showed an apparent underestimation of the AOD in different seasons (EE Below = 58.98%), but when the AOD range is small (0 < AOD < 0.1), the CALIPSO data accuracy is higher compared with other satellite products under small AOD range. In the South China Sea, VIIRS has higher data accuracy than MISR, while in the Bohai-Yellow Sea, East China Sea, Sea of Japan, and the western Pacific Ocean, MISR has the best data accuracy. MODIS and VIIRS show similar trends in R, EE within, MB, and RMSE under the influence of AOD, Angstrom exponent (AE), and precipitable water. The study on the temporal and spatial distribution of AOD in the East Asian Ocean shows that the annual variation of AOD is different in different sea areas, and the ocean in the coastal area is greatly affected by land-based pollution. In contrast, the AOD values in the offshore areas are lower, and the aerosol type is mainly clean marine type aerosol. These findings can help researchers in the East Asian Ocean choose the most accurate and reliable satellite AOD data product to better study atmospheric aerosols' impact and trends.

The Identification and Analysis of Long-Range Aerosol Transport Pathways with Layered Cloud-Aerosol Lidar with Orthogonal Polarization Datasets from 2006 to 2016

In this study, we used Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products acquired from 2006 to 2016 to identify global long-range aerosol transport pathways, including the trans-Atlantic, the trans-Pacific, and the trans-Arabian Sea pathways. Deep analyses were subsequently conducted focusing on two significant paths within the range of the trans-Pacific transport pathway, from which we generated a three-stage conceptual model mainly identifying aerosols from the Taklimakan Desert and aerosols from the North China Plain. The results show that in the first stage of the model, the dust or polluted-dust aerosols were emitted, raised, and mixed within the planetary boundary layer (PBL), characterized by high percentages (&gt;70%) of aerosols in the PBL (AODPBL), while in the second stage, some aerosols were further raised into the free troposphere where the AODPBL percentages decreased to less than 40%, driven by vertical movements and turbulences; in the last stage, the aerosols gradually settled back to the surface layer due to gravity and wet deposition, inferred by increasing AODPBL percentages. We demonstrated that the proposed model is capable of characterizing different aerosol types and climate conditions on spatiotemporal scales, providing a straightforward and evident approach to exploring long-range aerosol transport pathways.

Comparison of the Performance of the GRASP and MERRA2 Models in Reproducing Tropospheric Aerosol Layers

Two approaches, based on Generalized Retrieval of Aerosol and Surface Properties (GRASP) and Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) models, are investigated for reproducing aerosol layers in the troposphere. The GRASP algorithm is supplied with synergistic LIDAR and sunphotometer measurements to obtain aerosol extinction profiles. MERRA-2 is an atmospheric reanalysis coupling model that includes an external mixture of sea salt, dust, organic carbon, black carbon, and sulfate aerosols. A data set from Racibórz observatory, obtained with LIDAR and a sunphotometer in the 2017–2020 period, is analysed with GRASP along with the closest grid point data given by MERRA-2. The models demonstrate satisfactory agreement, yet some discrepancies were observed, indicating the presence of biases. For vertically integrated profiles, the correlation coefficient (R) between aerosol optical thickness was calculated to be 0.84, indicating a strong linear relationship. The Pearson correlation coefficient calculated between profiles for the selected altitude sectors varies between 0.428 and 0.824, indicating moderate to good agreement at all altitudes. GRASP shows denser aerosol layers in the mid-troposphere, while MERRA-2 gives higher aerosol extinctions throughout the high troposphere to low stratosphere region. Moreover, GRASP does not provide vertical variability in the extinction profile near the ground, due to a lack of data in the LIDAR’s incomplete overlap range. Lastly, the aerosol layer identification and type recognition are validated with statistical analysis of air mass backward trajectories with endpoints spatially and temporally collocated with individual identified layers. These reveal potential source regions that are located within areas known to be significant sources for the different identified aerosol types.

Validation and calibration of aerosol optical depth and classification of aerosol types based on multi-source data over China

A refined classification of aerosol types is essential to identify and control air pollution sources. This study focused on improving the resolution and accuracy of aerosol optical depth (AOD) and further refining the classification of aerosol types in China. We validated the accuracy of the AOD acquired using the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) and Copernicus Atmosphere Monitoring Service (CAMS) by comparing it with that acquired using from the Aeronet Robotic Network (AERONET). We simulated the AOD with high spatial resolution and accuracy based on the extremely randomized trees (ERT), adaptive boosting (AdaBoost), and gradient boosting decision trees (GBDT) models and identified aerosol types based on the Angstrom Exponent (AE) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the calibrated AOD. The results showed that CAMS overestimates AOD (21.4 %) and MERRA2 underestimates AOD (−17.3 %). Among the three machine learning models, the ERT model performed best, with a determination coefficient (R2) of 0.825 and the root-mean-square error (RMSE) of 0.174. Biomass burning/urban-industrial aerosols dominated China, with the largest contributions to southern, eastern, and central China in spring and summer. Clean continental aerosols contributed the most to southwestern China in fall and winter, whereas desert dust aerosols contributed the most to northwestern and eastern China in spring.

Climatology of aerosol types and their vertical distribution over Iran using CALIOP dataset during 2007–2021

The present study uses a Lidar-based aerosol type's extinction coefficient (EC) of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to investigate the spatio-temporal changes in the vertical cross section of aerosols from 2007 to 2021 in Iran. Aerosol characteristics i.e., the EC values (levels) and frequency are presented in a seasonal time scale. The trend of aerosol types EC in the vertical profile was estimated using Sen's slope estimator. Moreover a Pearson's correlation was employed to assess the link between climatic factors (temperature, pressure and relative humidity) and aerosol types EC. It is found that smoke followed by polluted continental have the largest EC levels than dust and polluted dust. The highest level and frequency of dust EC were observed in summer at an average altitude of 0.7 and 4.5 km, respectively in southern Iran. The highest level and greatest frequency of polluted continental were detected in summer and winter respectively at an altitude of below 2 km in the southern and northern polluted cities of Iran. The highest level and the greatest frequency of polluted dust EC were recorded in summer in the south of Iran at an average altitude of 4.5 km. Both the maximum smoke EC level and frequency were detected in winter and in the south of Iran at an average altitude of 4 km. A significant decreasing (increasing) trend of dust (polluted continental) EC was observed in spring and summer (summer) at an altitude below 5 (3) km in most regions (northern part) of Iran. Polluted dust showed an increasing trend in spring in most regions at an altitude below 5 km. The correlation between climatic factors and aerosol EC varied according to seasons, altitudes, and aerosol type. The common feature was the positive correlation between aerosol types EC and relative humidity in most regions, seasons and altitudes. In the final step, six polluted cities were analyzed for aerosol's trend and the correlations.

Estimation of Aerosol Layer Height from OLCI Measurements in the O2A-Absorption Band over Oceans

The aerosol layer height (ALH) is an important parameter that characterizes aerosol interaction with the environment. An estimation of the vertical distribution of aerosol is necessary for studies of those interactions, their effect on radiance and for aerosol transport models. ALH can be retrieved from satellite-based radiance measurements within the oxygen absorption band between 760 and 770 nm (O2A band). The oxygen absorption is reduced when light is scattered by an elevated aerosol layer. The Ocean and Land Colour Imager (OLCI) has three bands within the oxygen absorption band. We show a congruent sensitivity study with respect to ALH for dust and smoke cases over oceans. Furthermore, we developed a retrieval of the ALH for those cases and an uncertainty estimation by applying linear uncertainty propagation and a bootstrap method. The sensitivity study and the uncertainty estimation are based on radiative transfer simulations. The impact of ALH, aerosol optical thickness (AOT), the surface roughness (wind speed) and the central wavelength on the top of atmosphere (TOA) radiance is discussed. The OLCI bands are sufficiently sensitive to ALH for cases with AOTs larger than 0.5 under the assumption of a known aerosol type. With an accurate spectral characterization of the OLCI O2A bands better than 0.1 nm, ALH can be retrieved with an uncertainty of a few hundred meters. The retrieval of ALH was applied successfully on an OLCI dust and smoke scene. The found ALH is similar to parallel measurements by the Tropospheric Monitoring Instrument (TROPOMI). OLCI’s high spatial resolution and coverage allow a detailed overview of the vertical aerosol distribution over oceans.

Aerosol Optical Properties and Type Retrieval via Machine Learning and an All-Sky Imager

This study investigates the applicability of using the sky information from an all-sky imager (ASI) to retrieve aerosol optical properties and type. Sky information from the ASI, in terms of Red-Green-Blue (RGB) channels and sun saturation area, are imported into a supervised machine learning algorithm for estimating five different aerosol optical properties related to aerosol burden (aerosol optical depth, AOD at 440, 500 and 675 nm) and size (Ångström Exponent at 440–675 nm, and Fine Mode Fraction at 500 nm). The retrieved aerosol optical properties are compared against reference measurements from the AERONET station, showing adequate agreement (R: 0.89–0.95). The AOD errors increased for higher AOD values, whereas for AE and FMF, the biases increased for coarse particles. Regarding aerosol type classification, the retrieved properties can capture 77.5% of the total aerosol type cases, with excellent results for dust identification (&gt;95% of the cases). The results of this work promote ASI as a valuable tool for aerosol optical properties and type retrieval.

A comparison of atmospheric aerosol absorption properties from the MERRA-2 reanalysis with AERONET

Our focus is the comparison of atmospheric aerosol absorption properties between the MERRA-2 reanalysis and the inversion product of the surface station network AERONET. We use the available Aerosol Absorption Optical Depth (AAOD) and Single Scattering Albedo (SSA) data from both sources during the period 1993–2022, for the globe. The comparison is performed for the whole dataset, but also repeated for different classifications, namely by aerosol types, Köppen climate, and continent. Moreover, we investigate the relationships between these classifications. For these medium and high optical depth cases, the MERRA-2 relative bias for AAOD and SSA is globally −3.7% and −1.4%, but there is a wide differentiation in performance for the different types, climates, and continents. The MERRA-2 SSA frequency distribution is too narrow compared to the AERONET. MERRA-2 strongly overestimates the absorption over N. America and less so over S. America and Europe, while it underestimates it greatly over Oceania. AAOD is underestimated over biomass-burning regions and overestimated over most areas rich in dust. There is evidence that the lack of brown carbon in the aerosol type classification scheme in MERRA-2 hampers its performance. The comparison over Asia dry areas (classified as Köppen climate type B) shows a large underestimation in AAOD, non-existent in other dry (B) climate types. For the relatively few observations over polar (Köppen type E) climates, MERRA-2 gives too absorptive aerosols. With respect to absorption properties, it appears that MERRA-2 would improve its agreement with AERONET by addressing some erroneous aerosol classifications, employing the brown carbon type, and introducing more detail in dry region aerosol sources.

The Regional Aerosol Model Intercomparison Project (RAMIP)

Abstract. Changes in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from −0.3 to −1.5 W m−2. Both of these sources of uncertainty are exacerbated on regional scales. The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change. RAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality.

Spatial distribution of aerosols burden and evaluation of changes in aerosol optical depth using multi-approach observations in tropical region

Understanding of Aerosol optical depth (AOD) parameter is important for air quality assessment. This study aims to evaluate and validate AOD measurements from combine datasets to improve air quality for a period 2005–2020 using Aerosol Robotic Network (AERONET) at Ilorin site (8.320° N, 4.340° E) in Nigeria. AOD outputs from Community Atmosphere Model Version 6 with chemistry (CAM6-chem) at 1° horizontal resolution and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) are investigated in addition to validation of two satellites AOD retrievals: Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR). Result of spatial distribution of AOD shows high values > 1 in the North and Western Sahara compared to Central Africa. Desert dust shows largest contribution in the North and Western Africa that is up to 2 magnitude larger than other aerosol types. Primary organic matter (POM) and secondary organic aerosols (SOAs) both presents high burdens with later been dominant at around 10° band, and black carbon (BC) largest burden (2.6 × 10 − 5 kgm − 2) is seen in the model from oil and gas exploration site in Nigeria. Inter-comparison of MERRA/MISR/MODIS and AERONET AOD using linear correlation of the seasonal dependence demonstrated high correlation (r = 0.864 − 0.973) subjected to Root Mean Square Error (RMSE = 0.069 − 0.211), suggesting good agreement between the datasets. When compared to seasonal mean maximum AERONET AOD value of 0.978 MERRA is ∼5%, MISR ∼28% and MODIS ∼29% lower with stronger correlations observed in the wet and pre-harmattan seasons. Similarly, MODEL AOD at 550 nm and dust burden were found to be ∼34% and ∼67% lower in context to AERONET AOD annual mean value of 0.627. Positive relationships that indicate an upward slope exist between all the computed datasets with moderate value of AERONET/CAM-chem spearman partial correlation, and MERRA/MODIS and MODIS/MISR showing strong and significant relationship with p-value less than 0.05. Low variance is observed with all measurements except in MERRA.

Investigation of the effects of the Greek extreme wildfires of August 2021 on air quality and spectral solar irradiance

Abstract. In August 2021, a historic heatwave was recorded in Greece which resulted in extreme wildfire events that strongly affected the air quality over the city of Athens. Saharan dust was also transferred over Greece on certain days of the same period due to the prevailing southern winds. The impact of these events on air quality and surface solar radiation is investigated in this study. Event characterization based on active and passive remote sensing instrumentation has been performed. The study shows that significantly increased levels of air pollution were recorded from the end of July to the first week of August. The smoke led to unusually high aerosol optical depth (AOD) values (up to 3.6 at 500 nm), high Ångström exponent (AE) (up to 2.4 at 440–870 nm), and a strong and negative dependence of single-scattering albedo (SSA) on wavelength that was observed to decrease from 0.93 at 440 nm to 0.86 at 1020 nm, while the dust event led to high AOD (up to 0.7 at 500 nm), low AE (up to 0.9 at 440–870 nm), and a positive dependence of SSA on wavelength that was observed to increase from 0.89 at 440 nm to 0.95 at 1020. Furthermore, the smoke plume was also detected over the PANhellenic GEophysical observatory of Antikythera on 7 August, which is about 240 km away from Athens. Increased AOD values (up to ∼ 0.90 at 500 nm) associated with a high fine-mode AOD (up to ∼ 0.85 at 500 nm) and decrease in SSA with wavelength suggested the dominance of fine biomass burning aerosols. The impact of dust and smoke on solar irradiance revealed significant differences in the spectral dependence of the attenuation caused by the two different aerosol types. The attenuation of solar irradiance in the ultraviolet (UV-B) spectrum was found to be much lower in the case of dust compared to smoke for similar AOD500 values. Differences were less pronounced in the near-infrared and visible spectral regions. The large AODs during the wildfires resulted in a decrease in the noon UV index by up to 53 %, as well as in the daily effective doses for the production of vitamin D (up to 50 %), in the daily photosynthetically active radiation (up to 21 %) and in the daily global horizontal irradiance (up to 17 %), with serious implications for health, agriculture, and energy. This study highlights the wider impacts of wildfires that are part of the wider problem for Mediterranean countries, whose frequency is predicted to increase in view of the projected increasing occurrence of summer heatwaves.

Application of Gaussian Mixture Models for aerosol type analysis in China

The relative contributions of different aerosol types to the total aerosol content were determined using sun photometer derived inversion data from four Aerosol Robotic Network (AERONET) stations in China, i.e. Beijing, NUIST, Hong Kong PolyU and SACOL. Five main aerosol types were considered: dust (DU), mixed (MI), urban industry (UI), biomass burning (BB) and maritime (MA). The identification of these aerosol types is based on cluster analysis using Gaussian mixture models (GMMs), together with the Mahalanobis distance (MD) to each reference centroid. The results show that the aerosol types are distinctly different between the different sites as regards fine and coarse particles. MI is the dominant aerosol type at four locations, with the largest contribution at NUIST (73.4%). The largest contribution of DU (18.8%) is observed at SACOL and at Beijing the contribution of UI is largest (33.7%). BB contributions are relatively small, with the largest at NUIST (2.7%). For the analysis, two periods are considered, i.e. before and after the implementation of the national ambient air quality standard (GB3095–2012) in 2012. The clustering results revealed a changing trend in the proportion of UI and MI aerosols in Chinese cities. Although the proportion of UI aerosols has increased, MI aerosols still remain dominant. The proportion of DU in SACOL station also increased. The seasonal analysis shows that DU dominates in spring at the SACOL station (55.3%), which is near the dust source area. Among the other stations, the contribution of DU due to long-range transport from the source regions, is largest (10.6%) in Beijing, with a small contribution at NUIST. The aerosol volume size distributions in different regions exhibit substantial differences due to variations in aerosol types: Beijing and SACOL are dominated by coarse mode particles, while NUIST and Hong Kong PolyU are dominated by fine mode particles.

MODIS observations reveal decrease in lake suspended particulate matter across China over the past two decades

Variations in the concentrations and distribution of suspended particulate matter (SPM) of lakes can be used to show the responses of lake environment to climate and landscape change. However, the shifts and trends of SPM and potential drivers have not been well investigated across large spatial and temporal dimensions. This study developed a robust machine learning model to generate SPM time series in 269 lakes across China larger than 30 km2 from 2002 to 2021 using MODIS/Aqua imagery. The support vector regression model showed satisfactory performance on SPM retrievals over four orders of magnitude (0.1–1000 mg L−1) (mean absolute percentage error = 26%). The model performance was shown to be insensitive to changes in environmental and observing conditions (e.g., aerosol type and thickness, viewing geometry), based on a radiative transfer simulation model. The long-term MODIS record showed a spatial pattern of lower SPM in the western lakes compared to the shallow lakes of east China. Importantly, the SPM showed a significant decrease in the 21st century (average rate of change of −0.2 mg L−1/decade). The interannual variations in SPM were aggregated into five categories, ranging from lakes with continuous changing patterns to those with reversed changing patterns. The driving factors behind the changing patterns vary between different climate zones and ecoregions. A warmer and wetter climate was associated with decreasing SPM in western lakes, while the decrease in wind speed and reduced possibility of soil erosion were the primary drivers of progressively lower SPM in the eastern shallow lakes. These results not only show a comprehensive picture of the SPM dynamics of lakes in China but also provide new insights into the complex mechanisms that drive SPM spatiotemporal dynamics.

Aggregation-induced enhancements in aerosol absorption and scattering across the black-brown continuum

Global radiative forcing by carbonaceous aerosols is one of the largest sources of uncertainty in current climate models. The radiative impacts of brown carbon (BrC), a type of amorphous organic carbonaceous aerosol formed in biomass burning events, such as wildfires, remains poorly understood. Recently, the aggregation of spheres (monomers) of BrC was observed in wildfire smoke from various parts of the world. Aggregation could alter the optical properties and direct radiative forcing of BrC, yet very little is known about this phenomenon. This study improves upon the spectral optical properties of BrC aggregates observed in past field studies.We are motivated by the framework presented by Saleh et al. (2020) for the optical classification of carbonaceous particles across the black-brown continuum. Here, we simplify Saleh et al.'s BrC categorization into two sub-classes: dark brown carbon (d-BrC) and weakly-absorbing brown carbon (w-BrC). We calculate and compare the mass absorption cross-section (MAC), mass scattering cross-section (MSC), single scattering albedo (SSA), and asymmetry parameter (g) of d-BrC and w-BrC and determine their absorption and scattering enhancements due to aggregation. Polydisperse diffusion-limited cluster-cluster aggregation (p-DLCA) simulations generated 90 aggregates of varying monomer diameters, and discrete dipole approximation (DDA) was used to calculate optical properties of these aggregates at relevant refractive indices, monomer diameters, and incident wavelengths.We find that optical properties of BrC aggregates are more sensitive to the monomer number and mean diameter than to polydispersity. d-BrC has almost twice the MAC of w-BrC at 350 nm, but w-BrC has MSC values almost double that of d-BrC. Both MAC and MSC for both types of aerosol decrease with wavelength. Aggregation enhances optical properties, with smaller size parameters and lower imaginary part of the complex refractive index of aggregates resulting in stronger absorption and scattering.

Particle Microphysical Parameters and the Complex Refractive Index from 3β + 2α HSRL/Raman Lidar Measurements: Conditions of Accurate Retrieval, Retrieval Uncertainties and Constraints to Suppress the Uncertainties

We study retrieval methods in regard to their potential to accurately retrieve particle microphysical parameters (PMP) from 3β + 2α HSRL/Raman lidar measurements. PMPs estimated with these methods are number, surface-area and volume concentrations, the effective radius, and complex refractive index of the investigated particle size distribution (PSD). The 3β + 2α optical data are particle backscatter coefficients at 355, 532 and 1064 nm and extinction coefficients at 355 and 532 nm. We present results that are fundamental for our understanding of how uncertainties of the optical data convert into uncertainties of PMPs. PMPs can only be retrieved with preset accuracy if the input optical data are accurate to at least eight significant digits, i.e., 10−6%. Such measurement accuracy cannot be achieved by currently existing lidar measurement techniques and the fact that atmospheric conditions are not static during lidar observations. Our analysis of the results derived with the novel approach shows that (a) the uncertainty of the retrieved surface-area concentration increases proportionally to the measurement uncertainty of the extinction coefficient at 355 nm, (b) the uncertainty of the effective radius is inversely proportional to the measurement uncertainty of the extinction-related Ångström exponent, (c) the uncertainty of volume concentration is close to the one of the effective radius, and (d) the uncertainty of number concentration is proportional to the inverse of the square value of the uncertainty of the effective radius. The complex refractive index (CRI) cannot be estimated without introducing extra constraints, even if measurement uncertainties of the optical data are as low as 1−3%. We tested constraints and their impact on the solution space, and in how far these constraints could allow us to restrict the retrieval uncertainties. For example, we used information about relative humidity that can be measured with Raman lidar. Relative humidity is an important piece of information that allows for more accurate aerosol typing and thus plays a vital role in any kind of aerosol characterization. The measurement example we used in this study shows that such a constraint can reduce the retrieval uncertainty of single scattering albedo (SSA) to as low as ±0.01–±0.025 (at 532 nm), on the condition that the uncertainty of the input optical data stays below 15%. The results will be used for uncertainty analysis of data products provided by future versions of the Tikhonov Advanced Regularization Algorithm (TiARA). This algorithm has evolved into a standard tool for the derivation of microphysical particle properties from multiwavelength High-Spectral-Resolution Lidar (HSRL)/Raman lidar operated in Europe, East Asia, and the US.

Long-term analysis of AOD separated by aerosol type in East Asia

This study aimed to identify the temporal variations in aerosol loadings and sizes in East Asia based on a method that uses the linear particle depolarization ratio (δP) and coarse-mode fraction of volume concentration (CMFvc) from AERONET Sun/Sky radiometer data. East Asia is the polluted region. Pollution levels continue to increase as a result of population growth and increasing industrialization. The main pollution sources are derived from anthropogenic activities and Asian dust. The data were used to separate the total aerosol optical depths (τ) of mixed aerosol plumes into optical depths contributed by dust (τD), coarse- (τPC), and fine-mode pollution (τPF). We used data taken from 1999 to 2021 in East Asia (Beijing, Xianghe on the west, Seoul, Yonsei, Anmyon, and Gwangju in the middle, Osaka and Shirahama in the east, and Taipei in the south). We identified the regional differences; the contribution of τD and τPC to the total τ of Chinese sites was almost twice that of other East Asian sites. We analyzed the monthly, seasonal and annual values each of the three aerosol types contributed to total optical depth. The annual variations in τD and τPC from 1999 to 2021 showed a decreasing trend. In contrast, τPF either increased or became stagnant during that time. We conclude that aerosol types in East Asia may have changed. The Ångström exponent of fine-mode particles increased in most regions (0.0008–0.0103 yr−1 for the wavelength range 440–870 nm), which means the mean size of the fine-mode pollution particles tended to decrease, even though τPF increased. The change in particle size might be caused by the decrease in primary emission sources due to the strong air pollution reduction policies in China, Korea, and Japan. Therefore, we need to focus on the change in aerosol properties not just on aerosol loadings.

Analysis of Long‐Term Trends in the Vertical Distribution and Transport Paths of Atmospheric Aerosols in Typical Regions of China Using 15 Years of CALIOP Data

AbstractLong‐range transport and vertical distribution of aerosols are important factors for assessing the uncertainty in aerosol radiative forcing. This paper reveals the vertical distribution and trends of aerosol optical properties in China using 15 years of Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) data. The Hybrid Single‐Particle Lagrangian integrated trajectory model was used to analyze the transport and trends of aerosols in the layer with the highest occurrence frequencies of dust, polluted dust, polluted continental and elevated smoke aerosols. The results indicated that (a) there were significant regional and seasonal differences in the vertical distribution of aerosols. The aerosol optical depth (AOD) trend in a given region depends on the changes in the aerosol type with the highest frequency and the layer corresponding to the largest AOD in the vertical profile. The frequency of polluted dust aerosols was the highest in Beijing‐Tianjin‐Hebei (BTH) and Central China. The considerable decrease in the 0–2 km AOD led to a significant trend of the column AOD. (b) The changes of AOD and main aerosol types in a region are also affected by the changes of aerosol sources and long‐range transport pathways. In the BTH, dust aerosols originated from the Mongolian Plateau, accounting for 57.88% of the total trajectories. The Pearl River Delta was dominated by elevated smoke aerosols, with trajectories mainly originating from the Myanmar and Vietnam, accounting for 27.38% and 29.59%, respectively. The trend of 15‐year backward trajectories of dust aerosols on the Tibetan Plateau indicated that the trajectory from India is increasing.

Changing patterns in the highly contributing aerosol types/species across the globe in the past two decades

With the rapidly changing aerosol emissions due to the increase in urbanization, energy consumption, population density, and industrialization in the past two decades across the globe, there is an evolution of different chemical properties of aerosols that are yet not quantified properly. Therefore, a rigorous attempt is made in this study to obtain the long-term changing patterns in the contribution of different aerosol types/species, to the total aerosol loading. This study is carried out only over those regions exhibiting either increasing or decreasing trends in the aerosol optical depth (AOD) parameter on a global scale. Applying the multivariate linear regression trend analysis on Modern-Era Retrospective Analysis for Research and Application version 2 (MERRA-2) aerosol species dataset obtained between 2001 and 2020, we found that despite the overall statistically significant decrease in total columnar AOD trend values over North-Eastern America, and Eastern and Central China regions, an increase in the dust and organic carbon aerosols is observed, respectively. As the uneven vertical distribution of aerosols can alter the direct radiative effects, the extinction profiles of different aerosol types obtained using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) dataset between 2006 and 2020, are further partitioned, for the first time, based on their presence in different altitudes (i.e., within the atmospheric boundary layer and free-troposphere) as well as measurement timing (i.e., daytime and night-time) regimes. The detailed analysis showed that there exists an overall higher contribution of aerosols persisting in the free troposphere region which in turn can have a long-term effect on climate due to their higher residence time, particularly absorbing aerosols. As the trends are mostly associated with the changes in energy use, regional regulatory policies, and/or changing background meteorology conditions, therefore this study also elaborates on the effectiveness of these factors with the changes obtained in different aerosol species/types over the region.

A 1-year aerosol chemical speciation monitor (ACSM) source analysis of organic aerosol particle contributions from anthropogenic sources after long-range transport at the TROPOS research station Melpitz

Abstract. Atmospheric aerosol particles are a complex combination of primary emitted sources (biogenic and anthropogenic) and secondary aerosol resulting from aging processes such as condensation, coagulation, and cloud processing. To better understand their sources, investigations have been focused on urban areas in the past, whereas rural-background stations are normally less impacted by surrounding anthropogenic sources. Therefore, they are predisposed for studying the impact of long-range transport of anthropogenic aerosols. Here, the chemical composition and organic aerosol (OA) sources of submicron aerosol particles measured by an aerosol chemical speciation monitor (ACSM) and a multi-angle absorption photometer (MAAP) were investigated at Melpitz from September 2016 to August 2017. The location of the station at the frontier between western and eastern Europe makes it the ideal place to investigate the impact of long-range transport over Europe. Indeed, the station is under the influence of less polluted air masses from westerly directions and more polluted continental air masses from eastern Europe. The OA dominated the submicron particle mass concentration and showed strong seasonal variability ranging from 39 % (in winter) to 58 % (in summer). It was followed by sulfate (15 % and 20 %) and nitrate (24 % and 11 %). The OA source identification was performed using the rolling positive matrix factorization (PMF) approach to account for the potential temporal changes in the source profile. It was possible to split OA into five factors with a distinct temporal variability and mass spectral signature. Three were associated with anthropogenic primary OA (POA) sources: hydrocarbon-like OA (HOA; 5.2 % of OA mass in winter and 6.8 % in summer), biomass burning OA (BBOA; 10.6 % and 6.1 %) and coal combustion OA (CCOA; 23 % and 8.7 %). Another two are secondary and processed oxygenated OA (OOA) sources: less oxidized OOA (LO-OOA; 28.4 % and 36.7 %) and more oxidized OOA (MO-OOA; 32.8 % and 41.8 %). Since equivalent black carbon (eBC) was clearly associated with the identified POA factors (sum of HOA, BBOA, and CCOA; R2= 0. 87), eBC's contribution to each of the POA factors was achieved using a multilinear regression model. Consequently, CCOA represented the main anthropogenic sources of carbonaceous aerosol (sum of OA and eBC) not only during winter (56 % of POA in winter) but also in summer (13 % of POA in summer), followed by BBOA (29 % and 69 % of POA in winter and summer, respectively) and HOA (15 % and 18 % of POA in winter and summer, respectively). A seasonal air mass cluster analysis was used to understand the geographical origins of the different aerosol types and showed that during both winter and summer time, PM1 (PM with an aerodynamic diameter smaller than 1 µm) air masses with eastern influence were always associated with the highest mass concentration and the highest coal combustion fraction. Since during wintertime CCOA is a combination of domestic heating and power plant emissions, the summer contribution of CCOA emphasizes the critical importance of coal power plant emissions to rural-background aerosols and its impact on air quality, through long-range transportation.