This study investigates aerosol characteristics using ground-based measurements at two distinct regions, MohalKullu (31.9 degrees N, 77.12 degrees E; 1154 m amsl) and Kosi-Katarmal (29.64 degrees N, 79.62 degrees E; 1225 m amsl), from July 2019 to June 2022. The average Black Carbon (BC) concentrations were 1.5 f 1.0 mu g m- 3 at Mohal and 1.1 f 1.4 mu g m-3 at Katarmal. BC showed strong seasonal variability, with maxima during post-monsoon (2.6 f 1.0 mu g m- 3) and pre-monsoon (1.8 f 0.5 mu g m-3) seasons. The diurnal variation displayed distinct morning and evening peaks in all the seasons. High pre-monsoon AOD500 (0.30 f 0.06 to 0.54 f 0.08) and low values of & Aring;ngstrom exponent (0.67 f 0.10 to 0.95 f 0.30) indicated dominance of large particles, whereas lower AOD500 (0.21 f 0.07 to 0.25 f 0.03) in post-monsoon and winter, along with larger & Aring;ngstrom exponent (1.05 f 0.74 to 1.13 f 0.11), indicated smaller particles. Satellite-derived (OMI and MAIAC) AOD500 showed weak to moderate correlation with ground-based measurements at Mohal (R = 0.4639 for MAIAC, R = 0.1402 for OMI) and Katarmal (R = 0.3976 for MAIAC, R = 0.2980 for OMI). Using optical properties of aerosols and clouds (OPAC) and Santa Barbara discrete ordinate radiative transfer (SBDART) models, the short-wave aerosol radiative forcing (SWARF) was found negative at the surface and top of the atmosphere but positive in the atmosphere, suggesting significant surface cooling and atmospheric warming leading to high heating rates, respectively. Annual mean atmospheric radiative forcing was 27.36 f 6.00 Wm- 2 at Mohal and 21.87 f 7.26 Wm- 2 at Katarmal. These findings may have consequences for planning air pollution strategies and understanding the effects of regional climate change.

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.

Particulate matter (PM) is a vital pollutant that severely impacts human health, ecosystem well-being, and climate systems. In this review, the importance of vertical profiling is considered for understanding PM behavior between different layers of the atmosphere, and it includes modern techniques used such as meteorological towers and building methods, unmanned aerial vehicles (UAVs), aircraft, and satellite-based aerosol optical depth measurements. A systematic review was conducted, sourcing 150 articles published between 2000 and 2023, using relevant keywords such as Particulate Matter, Vertical Profiling, Environmental Impacts, and Climate Change from databases like Web of Science, Scopus, and Google Scholar. Key findings illustrate the vertical variations in PM levels associated with interactions among urban environments, meteorology, and specific atmospheric processes such as cloud formation, radiative forcing, and long-distance transport of pollutants. PM's effects on biodiversity, nutrient cycles, and ecosystem stability are also discussed. The environmental impacts of PM deposition, including biodiversity loss, nutrient cycling disruption, and ecosystem destabilization, elucidate widespread chronic anthropogenic particulate causes of long-term ecological damage around the globe. The study also examines relevant regulatory frameworks, specifically air quality standards, and policies, underpinning mitigation strategies. This review discusses how PM pollution is an increasingly alarming health risk. It reiterates the importance of demanding effective regulations on the local and global levels to counteract detrimental environmental and climatic consequences. This review clearly shows the immediate threats of PM. It should form a wake-up call to develop more effective monitoring tools and stringent regulatory measures against this omnipresent pollutant.

In South Asia, our understanding of atmospheric aerosols and their optical properties is limited, posing a challenge to comprehending climate change dynamics. This study characterises aerosol optical properties, radiative properties, black carbon (BC) and ozone (O3) at seven South Asian locations, including Nam Co (Tibetan Plateau, TP), Dhaka, Bhola (Bangladesh), and Hanimaadhoo, Kashidhoo, Male' and Gan (Maldives). The study utilises columnar aerosol data from the Aerosol Robotic Network (AERONET) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) from 2001 to 2020. Notably, during the winter, the highest Aerosol optical depth (AOD) levels were observed in Dhaka (1.0 +/- 0.5) and Bhola (0.8 +/- 0.4) among these seven locations. BC concentrations in Dhaka ranged from 2.1 to 2.8 mu g m-3, while Bhola recorded concentrations between 1.4 and 2.1 mu g m-3. O3 levels across Maldives sites remained consistent, with values ranging between 314 and 345 dobson units (DU), surpassing those in Bangladesh and TP. The analysis shows a significant difference in the rate at which the atmosphere heats (HR) up due to aerosols. Higher heating rates were observed over Kashidhoo during the post-monsoon and winter seasons, while lower values were seen during the pre-monsoon and monsoon seasons, compared with Hanimaadhoo and Male'. It is important to note that Bangladesh had higher HR values than the Maldives. This study helps us better understand the impact of atmospheric aerosols on South Asia's climate and the different seasonal patterns.

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.