Aerosols are an important factor leading to reduced visibility. In order to better comprehend the connection between visibility and aerosols, aerosol optical depth (AOD) and Angstrom exponent (AE) data from the Himawari-8 Advanced Himawari Imager (AHI) are used for validation in comparison with the data from the Aerosol Robotic Network (AERONET) observations in this paper, which amounted to 69,026 sets of data. The results indicate that the AOD of AHI is in good agreement with AERONET observations, but AE performs poorly. The correlation coefficients between the AOD of AHI and AERONET data increase with decreasing visibility and the root mean square error increase. The AE of AHI performs poorly in different visibility conditions. The conclusion drawn from further analysis of the correlation between aerosol products and meteorological factors is that the factor with the highest correlation with visibility. Mixed aerosols dominate at higher visibility and biomass burning/urban-industrial aerosols dominate at lower visibility. The visibility in a typical city (Beijing) has a strong negative correlation with AOD, a weak negative correlation with AE, and a strong correlation with aerosol radiative forcing. The reduction in visibility may be caused by the scattering and adsorption effects of aerosols. The results are important for the improvement and application of AHI aerosol products in regional pollution studies.

A comprehensive global investigation on the impact of reduction (changes) in aerosol emissions due to Coronavirus disease-2019 (COVID-19) lockdowns on aerosol single scattering albedo (SSA) utilizing satellite observations and model simulations is conducted for the first time. The absolute change in Ozone Monitoring Instrument (OMI) retrieved, and two highly-spatially resolved models (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated SSA is <4% (<0.04-0.05) globally during COVID (2020) compared to normal (2015-2019) period. Change in SSA during COVID is not significantly different from long-term and year-to-year variability in SSA. A small change in SSA indicates that significant reduction in anthropogenic aerosol emissions during COVID-19 induced lockdowns has a negligible effect in changing the net contribution of aerosol scattering and/or absorption to total aerosol extinction. The changes in species-wise aerosol optical depth (AOD) are examined in detail to explain the observed changes in SSA. Model simulations show that total AOD decreased during COVID-19 lockdowns, consistent with satellite observations. The respective contributions of sulfate and black carbon (BC) to total AOD increased, which resulted in a negligible change in SSA during the spring and summer seasons of COVID over South Asia. Europe and North America experience a small increase in SSA (<2%) during the summer season of COVID due to a decrease in BC contribution. The change in SSA (2%) is the same for a small change in BC AOD contribution (3%), and for a significant change in sulfate AOD contribution (20%) to total AOD. Since, BC SSA is 5-times lower (higher absorption) than that of sulfate SSA, the change in SSA remains the same. For a significant change in SSA to occur, the BC AOD contribution needs to be changed significantly (4-5 times) compared to other aerosol species. A sensitivity analysis reveals that change in aerosol radiative forcing during COVID is primarily dependent on change in AOD rather than SSA. These quantitative findings can be useful to devise more suitable future global and regional mitigation strategies aimed at regulating aerosol emissions to reduce environmental impacts, air pollution, and public health risks.

China is an important emitter of light-absorbing carbonaceous aerosols (LACs), including black carbon (BC) and brown carbon (BrC). Currently, there are large uncertainties in model-estimated direct radiative forcing (DRF) of LACs, partially due to the poor understanding of the emissions and optical properties of LACs. In this study, we estimated the DRF of LACs over China during the implementation of the Air Pollution Prevention and Control Action Plan (APPCAP) using the global chemical transport model (GEOS-Chem) coupled with the Rapid Radiative Transfer Model of GCMs (RRTMG). We updated the refractive index of BC, includedbiomass burning (BB) sources, biofuel (BF) and coal combustion (CC) sources in the residential sector as BrC emission sources and the optical properties were updated, which were not fully considered in the previous model studies. Our results showed that model could reasonably capture the spatial and temporal variations of LACs in China with the correlation coefficients between model simulated and Aerosol Robotic Network (AERONET) observed daily absorption aerosol optical depth (AAOD) of LACs at 440 nm above 0.63 and the corresponding values of the normalized mean bias within +/- 30%. The simulated annual mean LACs AAOD at 440 nm in China was 0.016 (0.021) in 2017 (2014) and BrC contributed about 20% (21%). The estimated annual mean clear-sky LACs DRF at the top of the atmosphere in China was 1.02 W m(-2) in 2017 and 1.38 W m(-2) in 2014, and the contribution of BrC was about 10% and 11%, respectively, which was dominated by the BF sources (46% in 2017 and 44% in 2014) and the BB sources (38% in 2017 and 43% in 2014), with CC sources being low (16% in 2017 and 13% in 2014). The annual mean AAOD and DRF of LACs in China decreased by 0.005 and 0.36 W m(-2) from 2014 to 2017, which were largely attributed to the reductions of anthropogenic emissions during the implementation of APPCAP. Our results would improve the understanding of the light absorption capacity and climate effects of LACs in China.

Fine particles (PM2.5) scatter and absorb solar radiation affecting the atmospheric temperature structure, and the effects vary with different concentrations and compositions. This study investigated the effect of PM2.5 on the urban temperature structure of Nanjing through concen- tration-and species-sensitive experiments using a box model. The results show that the optical parameters, atmospheric heating rate, radiative forcing, and temperature are affected by the PM2.5 concentration, PM2.5 composition, and relative humidity. Under 80% relative humidity, the asymmetry and single scattering albedo (SSA) were 0.7 and 0.88, while under 20% relative hu-midity, they were 0.6 and 0.77, respectively. PM2.5 increased the atmospheric heating rate by 1-18 K/day; while the surface temperature decreased with the presence of PM2.5. Furthermore, the heterogeneous concentration and composition distributions of PM2.5 led to changes in urban heat island (UHI) intensity. The UHI intensity could be reduced by 1-3 K by PM2.5, and the reduction increased with the increase in PM2.5 concentration and absorbing compositions. The existence of absorbing compositions and high concentrations of PM2.5 may work together to mask the UHI effect and other problems of urban development from 2000s till the present.

The decadal variability of direct radiative effects of aerosols is investigated at Dibrugarh, a site in northeast India (NEI) at the eastern Himalayan foothills, primarily using multi-wavelength solar radiometer measurements spanning from October 2001 to February 2020. The ground-based aerosol observations are combined with satellite remote sensing, reanalysis data, and model simulations to study the change in atmospheric particle loading over the region. Observations indicate a statistically significant increase (similar to 0.015 yr(-1)) in Aerosol Optical Depth (AOD) during the last two decades in line with an increase in human activity. As compared to 2001-2007 (we call it as Stage I), the aerosol burden has grown rapidly during 2008 until 2020 (Stage II). AOD at 500 nm is found to increase by similar to 40% from Stage I to Stage II, resulting in an increase in the aerosol direct radiative forcing (DRF) at the top of the atmosphere (TOA) by similar to 43% during stage II (similar to-16.0 W m(-2)), from the base value of -11.2 W m(-2) in Stage I. Decreasing biomass burning activities, black carbon aerosol mass concentration, and high sulfate and organic aerosols are the primary factors responsible for the trend in TOA cooling by-0.46 W m(-2) yr(-1). This is further aided by the decrease in rainfall over NEI. MERRA-2 data analysis shows a similar enhancements in aerosol load over the entire NEI and the adjacent highly polluted Indo-Gangetic Plains (IGP). A similar feature is seen over the IGP, primarily driven by anthropogenic emissions, but precedes that in NEI by about a year. A simulation of the regional climate model (RegCM) over the south Asian domain quantifies the contribution of aerosol loading over NEI due to the aerosols carried from the IGP. In the highest aerosol loading period, about 12-30% of the aerosols, equivalent to 15-30% of atmospheric warming, are transported from the IGP to the NEI.

Studies on optical properties of aerosols can reduce the uncertainty for modelling direct radiative forcing (DRF) and improve the accuracy for discussing aerosols effects on the Tibetan Plateau (TP) climate. This study investigated the spatiotemporal variation of aerosol optical and microphysical properties over TP based on OMI and MERRA2, and assessed the influence of aerosol optical properties on DRF at NamCo station (30 degrees 46.440N, 90 degrees 59.310E, 4730 m) in the central TP from 2006 to 2017 based on a long measurement of AERONET and the modelling of SBDART model. The results show that aerosol optical depth (AOD) exhibits obvious seasonal variation over TP, with higher AOD500nm (>0.75) during spring and summer, and lower value (<0.25) in autumn and winter. The aerosol concentrations show a fluctuated rising from 1980 to 2000, significant increasing from 2000 to 2010 and slight declining trend after 2013. Based on sensitivity experiments, it is found that AOD and single scattering albedo (SSA) have more important impact on the DRF compared with a values and ASY. When AOD440nm increases by 60%, DRF at the TOA and ATM is increased by 57.2% and 60.2%, respectively. When SSA440nm increases by 20%, DRF at the TOA and ATM decreases by 121% and 96.7%, respectively. (c) 2022 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Quantifying the concentration of absorbing aerosol is essential for pollution tracking and calculation of atmospheric radiative forcing. To quickly obtain absorbing aerosol optical depth (AAOD) with high-resolution and high-accuracy, the gradient boosted regression trees (GBRT) method based on the joint data from Ozone Monitoring Instrument (OMI), Moderate Resolution Imaging Spectro-Radiometer (MODIS), and AErosol RObotic NETwork (AERONET) is used for TROPOspheric Monitoring Instrument (TROPOMI). Compared with the ground-based data, the correlation coefficient of the results is greater than 0.6 and the difference is generally within +/- 0.04. Compared with OMI data, the underestimation has been greatly improved. By further restricting the impact factors, three valid conclusions can be drawn: 1) the model with more spatial difference information achieves better results than the model with more temporal difference information; 2) the training dataset with a high cloud fraction (0.1-0.4) can partly improve the performance of GBRT results; and 3) when aerosol optical depth (AOD) is less than 0.3, the perform of retrieved AAODs is still good by comparing with ground-based measurements. The novel finding is expected to contribute to regional and even urban anthropogenic pollution research.

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.

Given the advantages of remote sensing, an increasing number of satellite aerosol optical depths (AOD) have been utilized to evaluate near-ground PM2.5. However, the spatiotemporal relationship between AODs and PM2.5 still lacks a comprehensive investigation, especially in some regions with severe pollution within China. Here, we investigated the spatiotemporal relationships between several satellite AODs and the near-surface PM2.5 concentration across China and its 14 representative regions during 2016-2018 using the correlation coefficient (R), the PM2.5/AOD ratio (eta), the geo-detector (q), and the different aerosol-dominated regimes. The results showed that the MODIS AOD from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm strongly correlates with PM2.5 (R > 0.6) in China, particularly in the Chengyu (CY), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) regions. The close correlations (R = 0.7) exist between PM2.5 and MODIS and VIIRS AOD from the deep blue (DB) algorithm in the CY, BTH, and YRD regions. Under the key aerosols affecting China (e.g., sulfate and dust), there is a strong correlation (R > 0.5) between the PM2.5 and MODIS and VIIRS AODs from the MAIAC and DB algorithms, with the higher concentration of ground-level PM2.5 per unit of these AODs (eta > 130). The MAIAC AOD (Terra/Aqua) can better explain the spatial distribution (q > 0.4) of PM2.5 than those of AODs from the dark target (DT) and DB algorithms applied to the MODIS over China and its specific regions across seasons. The performance of the Advanced Himawari Imager (AHI) AOD (R > 0.5, q > 0.3) was close to that of the MAIAC AOD during the spring and summer; however, it was far less than the MAIAC AOD in the autumn and winter seasons. The investigation provides instructions for estimating the near-surface PM2.5 concentration based on AOD in different regions of China.

A continuing increase in droughts/floods in Asian monsoon regions and worsening air quality due to aerosols are the two biggest threats to the health and well being of over 60% of the world's population. This study focuses on in-situ observations of atmospheric aerosols and their impact on shortwave direct aerosol radiative forcing (SDARF) during the southwest monsoon season (June-September) from 2015 to 2020 over a semi-arid station in Southern India. The Standardized precipitation index (SPI) is used to identify the droughts and normal monsoon years. Based on the SPI index, 2015, 2016, and 2018 were considered the drought monsoon years, while 2017, 2019, and 2020 were chosen as the normal monsoon years. During the drought monsoon years (normal monsoon years), the monthly mean black carbon (BC) was 1.17 +/- 0.25 (0.72 +/- 0.18), 1.02 +/- 0.31 (0.64 +/- 0.17), 1.02 +/- 0.38 (0.74 +/- 0.28), and 1.28 +/- 0.35 mu g/m(3) (0.88 +/- 0.21 mu g/m(3)), for June, July, August and September respectively. The lower BC concentration during the normal monsoon years is mainly due to the enhanced wet-removal rates by high rainfall over the measurement location. In July, there was a high ventilation coefficient (VC) and low concentration of BC, while in September, low VC, and a high concentration of BC was observed in both the drought and the normal monsoon years. In addition, a plane-parallel radiative transfer model was used to estimate shortwave direct aerosol radiative forcing for composite and without BC at various surfaces, including the surface (SUF), atmosphere (ATM), and top of the atmosphere (TOA). During the drought monsoon years (normal monsoon years), the estimated monthly ATM forcing was 17.6 +/- 2.4 (13.9 +/- 2.1), 17.5 +/- 7.5 (12.7 +/- 4.4), 17.2 +/- 4.0 (13.5 +/- 1.9), and 17.4 +/- 2.8 Wm(-2) (14.6 +/- 0.7 Wm(-2)) for June, July, August, and September, respectively. During the drought monsoon years, the estimated BC forcing was substantially larger (8.8 +/- 2.6 Wm(-2)) than that of normal monsoon years (6.0 +/- 1.5 Wm(-2)). It indicates the important role of absorbing BC aerosols during the drought monsoon years in introducing additional heat to the lower atmosphere, particularly over peninsular India.