From the beginning of May 2023 to the end of August 2023, the Northern Hemisphere experienced significant wildfire activity with the most widespread fires occurring in Canada. Forest fires in Canada destroyed more than 15.6 million hectares of forests. These wildfires worsened air quality across the region and other parts of the world. The smoke reached southern Europe by the end of June 2023. To better understand the consequences of such forest fires far from the site of origin, aerosol optical, microphysical and radiative properties were analyzed during this event for southern Europe using data from the Visible Infrared Imaging Radiometer Suite (VIIRS), TROPOspheric Monitoring Instrument (TROPOMI), and Aerosol Robotic Network (AERONET). TROPOMI aerosol index (AI) and the carbon monoxide (CO) product confirm that the smoke originated directly from these forest fires. AERONET data from the El Arenosillo site in southern Spain showed maximum aerosol optical depth (AOD) values on June 27 reached 2.36. Data on Angstrom Exponent (AE), aerosol volume size distribution (VSD), single scattering albedo (SSA), fine mode fraction (FMF), volume particle concentration, effective radius (R Eff ), absorption AOD (AAOD), extinction AE (EAE) and absorption AE (AAE) showed that fine-mode particles with carbonaceous aerosols contribution predominated in the atmosphere above the El Arenosillo site. Direct aerosol radiative forcing (DARF) at the top (DARF TOA ) and bottom of atmosphere (DARF BOA ) were-103.1 and-198.93 Wm-2 , respectively. The atmospheric aerosol radiative forcing (DARF ATM ) was found to be 95.83 Wm-2 and with a heating rate 2.69 K day-1 , which indicates the resulting warming of the atmosphere.

Objective Light-absorbing aerosols have a huge impact on visibility. The atmospheric pollution they cause can pose serious risks to human health. Quantitatively assessing the optical properties and spatiotemporal distribution of light-absorbing aerosols is of vital importance for decision-making in the management and control of complex air pollution. The dynamic changes in the physicochemical properties of light-absorbing aerosols, along with their temporal and spatial heterogeneity, introduce significant uncertainties in simulating their radiative forcing. The challenges arise from difficulties in accurately estimating particle size distribution, chemical composition, and mixed state, impeding precise retrievals through satellite remote sensing, with common model simulations and radiative transfer equations assuming the presence of external mixing for light-absorbing aerosols. However, research indicates that, especially in regions prone to pollution events like East Asia, South Asia, and Southeast Asia, a core-shell mixed state, with black carbon as the core and scattering aerosols like sulfates and nitrates as the shell, best represents the prevailing state of light-absorbing aerosols. Rough assumptions about aerosol states not only introduce significant errors in simulating aerosol number and mass concentrations in the atmosphere but also lead to substantial uncertainties in estimating overall radiative forcing. Methods Data from both satellite and in situ measurements are employed in the present study. First, we employ the AERONET aerosol optical depth (AOD) dataset to identify polluted days at three selected sites, and we match it in space and time with the single scattering albedo (SSA) dataset combined with the TROPOMI ultraviolet (UV) SSA dataset. Second, we utilize the Mie optical model across various combinations of core and shell sizes to establish a preliminary SSA map. Subsequently, we use SSA data from six different wavebands to constrain the SSA output from the Mie model. All calculations are conducted at a daily and grid-level resolution. Upon obtaining probability distributions for core size, shell size, and their corresponding SSA and absorption coefficient (ABS) values, we then apply spatial relationships between the column total absorbing aerosol optical depth (AAOD) from TROPOMI, single-particle absorption, and size distribution. This allows us to assess the column value of black carbon mass concentration and particle number concentration. Results and Discussions Spatial distribution of the mean absorption coefficient obtained from the Mie model simulations during periods of severe pollution shows that the absorption coefficient of the Beijing station is generally higher, with values mainly concentrated between 0. 05 and 0. 07. This indicates a higher presence of light-absorbing aerosols during this period. For the Hong Kong station, most of the absorption coefficients are below 0. 1, with the majority falling below 0. 2 and a low standard deviation of less than 0. 02. Factors related to topography and wind patterns are the primary reasons for the lower values observed in the Hong Kong station (Fig. 3). After applying spatial relationships between the column total AAOD from TROPOMI, the results show that the particle concentrations in the column at the Beijing station generally fall within the range of 3 x 10(19)-5 x 10(19) grid(-1). The number concentrations in Hong Kong are relatively lower than those in Beijing. Except for a few grid points where concentrations reach 2. 5 x 10(19) grid(-1), the overall value range in Hong Kong between 1 x 10(19) and 2 x 10(19) grid(-1). For the Seoul station, particle concentration range is from 1. 5 x 10(19) to 3. 0x 10(19) grid(-1) (Fig. 4). By considering the particle size distribution of black carbon aerosols under the core-shell mixed state simulated by the Mie model, the results of the spatial distribution of black carbon aerosol column mass concentration at each grid point (Fig. 6) shows that over 60% of the area of Beijing have concentrations exceeding 500 kg/grid. In the Hong Kong area, apart from certain regions within the Pearl River Delta urban cluster where black carbon column mass exceeds 500 kg/grid, the values in other areas are below 300 kg/grid. In addition, Seoul has an overall column mass concentration of less than 300 kg/grid.

The aerosol particles present in the atmospheric region mainly affect the climate radiative forcing directly by scattering & absorbing the sunlight. Also, it indirectly influences the formation of clouds, precipitation and acts as a considerable uncertainty in assessing Earth's radiation budget. Determination of aerosol type is significant in characterizing the aerosol role in the atmospheric processes, feedback, and climate models. This paper proposes two aerosol classification models, one based on the source and another based on the composition, to classify the aerosols using aerosol optical properties. The source based aerosol classification method helps to identify the sources which cause pollution in a particular region. Based on the results, proper control measures can be taken to reduce pollution. The composition based aerosol classification helps to identify the nature of aerosol types, such as absorbing or non-absorbing. This classification helps to study the climate of the Kanpur region. The aerosol data is taken from AERONET (AErosol RObotic NETwork) for the period 2002-2018 for the Kanpur region. The composition based aerosol classification model uses Single Scattering Albedo (SSA), Angstrom Exponent (AE), and Fine Mode Fraction (FMF) parameters to categorize aerosols based on their composition. The source based aerosol classification model classifies the aerosols based on values of AE and Aerosol Optical Depth (AOD) and describes the source of the aerosol particles. Knowledge of aerosol sources and compositions helps execute policies or controls to reduce aerosol concentrations. Machine learning algorithms, Nai center dot ve Bayes, K Nearest Neighbor, Decision Tree, Support Vector Machine, and Random Forest are used to validate classification schemes. The performance analysis of machine learning algorithms is compared using ten different metrics, and the results are also compared with the existing aerosol classification models. The results of the classification show that the source based aerosols of the desert and arid background and the composition based aerosols of types, Mixture Absorbing, Coarse absorbing (Dust), and Black Carbon are dominant over the Kanpur region during the study period considered. The Number of non -absorbing (scattering) type aerosols are least in the study region considered during the study period at all the seasons. It is found that the Random Forest and Decision Tree models outperform the other machine learning models considered and the existing classification models in terms of accuracy (99.55 %) and other performance metrics considered.(c) 2023 COSPAR. Published by Elsevier B.V. All rights reserved.

Aerosols play an important role in the earth's environment across the globe through their involvement in various earth system cycles. The change in the aerosol properties may cause short and long-term impacts, the knowledge of such changes is useful in the estimation of the pollution sources of any region. We have carried out the analysis of the aerosols' optical and radiative properties using AERONET station data from 2018 to 2021 in Dibrugarh City. The higher Aerosol Optical Depth (AOD) values during winter and pre-monsoon months indicate high anthropogenic activities, and biomass burning in Dibrugarh. The impact of various sources and daily meteorological parameters help in understanding the diurnal variations of the AOD, Angstrom Exponent (AE), and column water (CW). Fine aerosol fractions dominate the aerosol volume, but sometimes the long-range transport of dust affects aerosol properties during pre-monsoon months (MAM). MODIS-derived AOD and AERONET AOD values show a good correlation, with R-2 = 0.68. The highest volume of the aerosols reaches up to 0.11 mu m(3) mu m(-2) during pre-monsoon months, whereas it lies below 0.05 mu m(3) mu m(-2) in other seasons. SSA values indicate the presence of scattering aerosols but in 2020, a sudden decline in the SSA values shows a strong rise in the absorbing aerosols. Throughout the study period (2018-2021), the positive radiative forcing indicates a rise in atmospheric heating.

Absorbing aerosols have significant influences on tropospheric photochemistry and regional climate change. Here, the direct radiative effects of absorbing aerosols at the major AERONET sites in East Asia and corresponding impacts on near-surface photochemical processes were quantified by employing a radiation transfer model. The average annual aerosol optical depth (AOD) of sites in China, Korea, and Japan was 1.15, 1.02 and 0.94, respectively, and the corresponding proportion of absorbing aerosol optical depth (AAOD) was 8.61%, 6.69%, and 6.49%, respectively. The influence of absorbing aerosol on ultraviolet (UV) radiation mainly focused on UV-A band (315-400 nm). Under the influence of such radiative effect, the annual mean near-surface J[NO2] (J[(OD)-D-1]) of sites in China, Korea, and Japan decreased by 16.95% (22.42%), 9.61% (13.55%), and 9.63% (13.79%), respectively. In Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) region, the annual average AOD was 1.48 and 1.29, and the AAOD was 0.14 and 0.13, respectively. The UV radiative forcing caused by aerosols dominated by black carbon (BC-dominated aerosols) on the surface was -3.19 and -2.98 W m(-2), respectively, accounting for about 40% of the total aerosol radiative forcing, indicating that the reduction efficiency of BC-dominated aerosols on solar radiation was higher than that of other types of aerosols. The annual mean J[NO2] (J[(OD)-D-1]) decreased by 14.90% (20.53%) and 13.71% (18.20%) due to the BC-dominated aerosols. The daily maximum photolysis rate usually occurred near noon due to the diurnal variation of solar zenith angle and, thus, the daily average photolysis rate decreased by 2-3% higher than that average during 10:00-14:00.

East Africa (EA) suffers from the inadequate characterization of atmospheric aerosols, with far-reaching consequences of its inability to quantify precisely the impacts of these particles on regional climate. The current study aimed at character-izing absorption and radiative properties of aerosols using the long-term (2001-2018) AErosol RObotic NETwork (AERONET) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data over three environ-mentally specific sites in EA. The annual mean absorption aerosol optical depth (AAOD440 nm), absorption Angstrom Ex-ponent (AAE440-870 nm), total effective radius (REff), and total volume concentration (mu m3/mu m2) revealed significant spatial heterogeneity over the domain. The study domain exhibited a significant contribution of fine-mode aerosols com-pared to the coarse-mode particles. The monthly variation in SSA440 nm over EA explains the strength in absorption aero-sols that range from moderate to strong absorbing aerosols. The aerosols exhibited significant variability over the study domain, with the dominance of absorbing fine-mode aerosols over Mbita accounting for similar to 40 to similar to 50 %, while weakly absorbing coarse-mode particles accounted for similar to 8.2 % over Malindi. The study conclusively determined that Mbita was dominated by AAOD mainly from biomass burning in most of the months, whereas Malindi was coated with black carbon. The direct aerosol radiative forcing (DARF) retrieved from both the AERONET and MERRA-2 models showed strong cooling at the top of the atmosphere (TOA; -6 to -27 Wm-2) and the bottom of the atmosphere (BOA, -7 to -66 Wm-2). However, significant warming was noticed within the atmosphere (ATM; +14 to +76 Wm-2), an indica-tion of the role of aerosols in regional climate change. The study contributed to understanding aerosol absorption and ra-diative characteristics over EA and can form the basis of other related studies over the domain and beyond.

According to the particle size and absorptivity as determined by the fine mode fraction and the single-scattering albedo (SSA) retrievals from AErosol RObotic NETwork (AERONET) sites around the world, aerosols are classified into four key categories: coarse and absorptive aerosol (Type I), mixed aerosol (Type II), fine and absorptive aerosol (Type III), fine and non-absorptive aerosol (Type IV). Seasonal variations of aerosol types with their corresponding direct radiative forcing efficiency (RFE) are observed on different continents. The RFE at the surface (RFEsfc) and top of the atmosphere (RFEtoa) reach their maximum (minimum) values over Asia and North America (Europe, Oceania, and South America) from June to August. The effects of solar zenith angle (SZA), surface albedo (SA), and SSA on RFEsfc and RFEtoa are investigated. The absolute values of RFE at TOA of all types of aerosols are largest at cos(SZA) =0.3 to 0.4. The increased SA reduces the absolute value of RFE both at SFC and TOA for all types of aerosols, and when SA reaches a specific threshold, depending on the type of aerosol, the RFEtoa turns positive. RFEtoa increases while RFEsfc decreases with decreasing SSA. The RFEsfc of the four categories of aerosol varies slightly in the same SZA, SSA and SA conditions, while RFEtoa is aerosol type dependent. It is found that larger particles reflect more solar energy into space per optical depth, resulting in an enhanced cooling effect under similar SZA, SSA, and SA conditions.

A comprehensive investigation of physical, optical, and chemical characteristics of columnar aerosols over two locations with distinct environmental settings in the Indo-Gangetic Plain (IGP) region, namely, Kanpur (urban and industrial area) and Gandhi College (rural area), is conducted using high-quality aerosol datasets obtained from ground-based Aerosol Robotic Network (AERONET) observations during the recent five year period (2015-2019). This study utilizes all the crucial columnar aerosol parameters necessary for accurately estimating aerosol radiative forcing. Quantification of contribution by different aerosol species originating from natural and anthropogenic sources to the total aerosol optical depth (AOD) and single scattering albedo (SSA) is important to understand the specific mechanisms that influence the aerosol composition, thereby reducing the uncertainty in aerosol radiative forcing. For the first time, two highly spatially resolved models' (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated absorbingspecies-wise (black carbon (BC), dust, and brown carbon (BrC)) AOD, and absorption AOD (AAOD) are compared and contrasted against the AERONET observations over the IGP region in a systematic manner. MERRA-2 AODs are mostly lower, whereas CAMS AODs are consistently higher than the AERONET AODs. A comparison of collocated time and space observations with models clearly suggests that improvements in emission inventories on a seasonal scale are essential. MERRA-2 SSA is noted lower than the AERONET SSA during the winter season due to overestimation in BC AOD. During winter in >70% of MERRA-2 simulated SSA the difference is higher than +/- 0.03 (the uncertainty range of AERONET SSA) whereas during pre-monsoon and monsoon seasons >60% of MERRA-2 SSA lies within the uncertainty range of AERONET SSA. Both models show a gradient in AODDust decreasing from west to east in the IGP. However, observations do not often exhibit the gradient in dust, which is validated by air mass back trajectory analyses as air masses travel through different pathways to IGP and reverse the west to east gradient in AODDust. This quantitative and comparative collocated analysis of observed aerosol characteristics with models on a seasonal scale will enable a better estimation of aerosol radiative forcing, and can help improve aerosol processes and parameterizations in models.

The Tibetan Plateau (TP), as a remote and sparsely populated area, is regularly exposed to polluted air masses sourcing from surrounding regions. Atmospheric circulation, as the major driving force generating long-range transport processes of air pollutants, contributes to high-pollution episodes on the TP. Therefore, using reanalysis data from the European Centre for Medium-Range Weather Forecasts for the 2000-2019 period, this paper first classified atmospheric circulation patterns over the study area into nine types (type 1 - type 9). Among them, circulation types 1, 2, 6, and 8 mainly occurred in spring and winter, while circulation types 3, 4, 5, 7, and 9 primarily occurred in summer and autumn. Second, ground-based and satellite remote sensing data were combined to investigate the impact of atmospheric circulation patterns on the properties of aerosols over Central West Asia and their surrounding areas. We detailed how the atmospheric circulation patterns impacted the aerosol optical depth, angstrom ngstro center dot m exponent, and aerosol types at different Aerosol Robotic Network sites in the study area. The results obtained from ground-based data were further verified by those from satellite remote sensing data. Third, backward trajectories and the corresponding potential source contribution function based on the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were used to explore the impact of atmospheric circulation patterns on regional transport pathways of aerosols. It was found that under circulation types 1, 2, 6, and 8, few HYSPLIT trajectories were sourced from the south direction, while under circulation types 3, 4, 5, 7, and 9, the trajectories originating from the south increased significantly, which could be attributed to the summer monsoon.

Atmospheric aerosols affect human health, alter cloud optical properties, influence the climate and radiative balance, and contribute to the cooling of the atmosphere. Aerosol climatology based on aerosol robotic network (AERONET) and ozone monitoring instrument (OMI) data from two locations (Urban Dhaka and coastal Bhola Island) over Bangladesh was conducted for 8 years (2012- 2019), focusing on two characterization schemes. Four aerosol parameters, such as extinction angstrom exponent (EAE), absorption AE (AAE), single scattering albedo (SSA), and real refractive index (RRI), were exclusively discussed to determine the types of aerosol. In addition, the light absorption properties of aerosol were inspected tagging the association between size parameters similar to fine mode fraction (FMF), AE, and absorption parameters (SSA and AAE). Results of aerosol absorption optical depth (AAOD) were validated with the satellite-borne cloud-aerosol lidar and infrared pathfinder satellite observation (CALIPSO) aerosol subtype profiles. The overall average values of AAOD for Dhaka and Bhola were (0.110 +/- 0.002) [0.106, 0.114] and (0.075 +/- 0.001) [0.073, 0.078], respectively. The values derived by OMI were the similar (0.024 +/- 0.001 [0.023, 0.025] for Dhaka, and 0.023 +/- 0.001 [0.023, 0.024] for Bhola). Two types of aerosols were potentially identified, for example, biomass burning and urban/industrial types over Bangladesh with insignificant contribution from the dust aerosol. Black carbon (BC) was the prominent absorbing aerosol (45.9%-89.1%) in all seasons with negligible contributions from mixed BC and/or dust and dust alone. Correlations between FMF and SSA confirmed that BC was the dominant aerosol type over Dhaka and Bhola. CALIPSO's vertical information was consistent with the AERONET column information. The results of aerosol parameters will have a substantial impact on the aerosol radiative forcing, and climate modeling as well as air quality management in Southeast Asia's heavily polluted territories.