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.

In context with the scientific evidence of aerosol deposition induced snow and glacier melt, this paper provides baseline information about the spatiotemporal variability of aerosols and snow-ice chemistry filling the data and knowledge gap over the western Himalaya, India based on recently published paper [ 1 ]. A systematic approach was employed that entailed analysis of aerosol variability over four decades using MERRA-2 (Modern-Era Retrospective analysis for Research and Applications) data over five major mountain ranges in the western Himalaya. Further, data about nine physicochemical parameters was generated over three selected glaciers in the study area. HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model simulated air mass sources at weekly intervals. This dataset is valuable for future investigations aimed at understanding and characterizing the impacts of light-absorbing impurities on radiative forcing, albedo changes, snow-melt, glacier recession and wa- ter quality in the western Himalaya. (c) 2024 Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

This article investigates the snow albedo changes in Colombian tropical glaciers, namely, Sierra Nevada de Santa Marta (SNSM), Sierra Nevada del Cocuy (NSC), Nevado del Ruiz (NDR), Nevado Santa Isabel (NDS), Nevado del Tolima (NDT), and Nevado del Huila (NDH). They are associated with the possible mineral dust deposition from the Sahara Desert during the June and July months using snow albedo (SA), snow cover (SC), and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites. And mineral dust (MD) from The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), both of them during 2000-2020. Results show the largest snow albedo reductions were observed at 39.39%, 32.1%, and 30.58% in SNC, SNSM, and NDR, respectively. Meanwhile, a multiple correlation showed that the glaciers where MD contributed the most to SA behavior were 35.4%, 24%, and 21.4% in NDS, NDC, and NDR. Results also display an increasing trend of dust deposition on Colombian tropical glaciers between 2.81 x 10-3 & mu;g & BULL;m-2 & BULL;year-1 and 6.58 x 10-3 & mu;g & BULL;m-2 & BULL;year-1. The results may help recognize the influence of Saharan dust on reducing snow albedo in tropical glaciers in Colombia. The findings from this study also have the potential to be utilized as input for both regional and global climate models. This could enhance our comprehension of how tropical glaciers are impacted by climate change.

Aerosol direct radiative forcing (ADRF) has substantial impacts on regional and global climate changes, whereas it remains one of the largest uncertainties among various climate forcing factors. The 40-year detailed clear-sky ADRFs over China from 1981 to 2020 are systematically studied based on the MERRA-2 satellite reanalysis data, which hopefully benefit for the evaluation of the performances of aerosol-climate models. The clear-sky short-wave ADRFs show diverse spatial distributions with strong top of atmosphere (TOA) and surface cooling and atmospheric heating over the Taklamakan desert, eastern China, and southern China. A high clear-sky longwave surface ADRF reaching-6.5 W/m2 over dust source regions is found, and continuous increase of ADRFs over the Taklamakan desert during the past four decades may indicate that dust episodes therein are becoming severe. The mean clear-sky shortwave surface, TOA and atmospheric ADRFs, and longwave surface ADRF over China during 1981-2020 are found to be-12.3,-5.1, 7.2, and 1.0 W/m2, respectively. The seasonality of clear-sky ADRFs shows strongest mean values in spring, moderate forcings in summer and fall, and weakest levels in winter. The monthly average clear-sky surface and TOA ADRFs over China vary by approximately twofold, ranging the weakest values of-7.8 and-3.9 W/m2 in December to the strongest-17.6 and-7.1 W/m2 in April, respectively. Distinctive seasonal and monthly patterns of clear-sky ADRFs are generally seen among the Beijing -Tianjin-Hebei region, Yangtze River Delta, Pearl River Delta and Tarim Basin in China, while the monthly ADRF patterns over a typical area of these four regions are similar during four different decades. The clear-sky ADRFs over China are highly correlated with aerosol optical thickness, and dust has strong influences on clear-sky shortwave aerosol direct radiative forcing among column aerosol compositions. Our study indicates general underestimations of clear-sky atmospheric ADRF over China by aerosol-climate models and stronger impacts of aerosol scattering than absorption on the TOA radiation budgets in China.

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 second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) land surface temperature (LST) dataset has been widely used for permafrost mapping in specific areas; however, its accuracy and application need to be evaluated over China. In this study, the MERRA-2 LST was evaluated against meteorological observations and three other reanalysis datasets including the first-generation MERRA, Japanese 55-year Reanalysis (JRA-55), and European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), using multiple statistical methods over the period from 1980 to 2018. The results revealed that the MERRA-2 LST generally exhibited cold bias compared to meteorological observations while performing better than the JRA55, ERA-Interim, and MERRA datasets in China, particularly in high-altitude permafrost regions. The comparison indicated that the time series trends for the MERRA-2 LST was consistent with that observed until 2000, and noticeably amplified cold bias, particularly for the period after 2005, was observed. Moreover, two correction methods were proposed and compared to reduce the error range for the MERRA-2 dataset, which was caused by the difference in elevation and land cover types. Calibrated results demonstrated that the linear regression method (Method1) between the elevation difference and mean bias error (MBE) for the LST performed well with root mean square error (RMSE) ranged from 2.15 to 5.97 ?C to 1.09-2.53 ?C. Moreover, in comparison with the MODIS LST dataset, the results showed that the adjusted MERRA-2 LST was in good agreement with smaller RMSEs against the observations. The surface frost number model was used for mapping the permafrost distribution over China based on the daily adjusted MERRA-2 LST dataset. According to the simulation results, the permafrost extent had a slightly continued degradation trend with a rate of 3-5% per decade over the past 39 years. The simulated permafrost area over China for the years 2010-2018 was approximately 1.63 x 106 km2, which accounts for 16.9% of mainland China. Thus, the adjusted MERRA-2 LST with high spatial-temporal consistency is the optimal choice to investigate permafrost distribution on a large scale.

Multi year measurements of surface-reaching solar (shortwave) radiation fluxes across a network of aerosol observatories (ARFINET) are combined with concurrent satellite (CERES)-based top of the atmosphere (TOA) fluxes to estimate regional aerosol direct radiative forcing (ARF) over the Indian region. The synergistic approach improves the accuracy of ARF estimates, which otherwise results in an overestimation or underestimation of the atmospheric forcing. During summer, an overestimation of similar to 5 W m(-2) (corresponding heating rate similar to 0.15 K day(-1)) is noticed. The regional average ARF from the synergistic approach reveals the surface forcing reaching -49 W m(-2) over the Indo Gangetic Plains, -45 W m(-2) over northeast India, -34 W m(-2) over the southern Peninsula, and - 16 W m(-2) in the oceanic regions of the Bay of Bengal. The ARF over the northern half of the Indian subcontinent is influenced mainly by anthmpogenic sulfate and carbonaceous aerosols. Dust is dominant in the western region of India during MAM and JJAS. Overall, the clear sky surface reaching solar radiation fluxes is reduced by 3-22% due to the abundance of aerosols in the atmosphere, with the highest reduction over the IGP during autumn and winter.

Biomass burnings either due to Hazards Reduction Burnings (HRBs) in late autumn and early winter or bushfires during summer periods in various part of the world (e.g., CA, USA or New South Wales, Australia) emit large amount of gaseous pollutants and aerosols. The emissions, under favourable meteorological conditions, can cause elevated atmospheric particulate concentrations in metropolitan areas and beyond. One of the pollutants of concern is black carbon (BC), which is a component of aerosol particles. BC is harmful to health and acts as a radiative forcing agent in increasing the global warming due to its light absorption properties. Remote sensing data from satellites have becoming increasingly available for research, and these provide rich datasets available on global and local scale as well as in situ aethalometer measurements allow researchers to study the emission and dispersion pattern of BC from anthropogenic and natural sources. The Department of Planning, Industry and Environment (DPIE) in New South Wales (NSW) has installed recently from 2014 to 2019 a total of nine aethalometers to measure BC in its state-wide air quality network to determine the source contribution of BC and PM2.5(particulate Matter less than 2.5 mu m in diameter) in ambient air from biomass burning and anthropogenic combustion sources. This study analysed the characteristics of spatial and temporal patterns of black carbon (BC) in New South Wales and in the Greater Metropolitan Region (GMR) of Sydney, Australia, by using these data sources as well as the trajectory HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) modelling tool to determine the source of high BC concentration detected at these sites. The emission characteristics of BC in relation to PM(2.5)is dependent on the emission source and is analysed using regression analysis of BC with PM(2.5)time series at the receptor site for winter and summer periods. The results show that, during the winter, correlation between BC and PM(2.5)is found at nearly all sites while little or no correlation is detected during the summer period. Traffic vehicle emission is the main BC emission source identified in the urban areas but was less so in the regional sites where biomass burnings/wood heating is the dominant source in winter. The BC diurnal patterns at all sites were strongly influenced by meteorology.

A change in soil temperature (ST) is a significant indicator of climate change, so understanding the variations in ST is required for studying the changes of the Qinghai-Tibet Plateau (QTP) permafrost. We investigated the performance of three reanalysis ST products at three soil depths (0-10 cm, 10-40 cm, and 40-100 cm) on the permafrost regions of the QTP: the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim), the second version of the National Centers for Environmental Prediction Climate Forecast System (CFSv2), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results indicate that all three reanalysis ST products underestimate observations with negative mean bias error values at all three soil layers. The MERRA-2 product performed best in the first and second soil layers, and the ERA-Interim product performed best in the third soil layer. The spatiotemporal changes of annual and seasonal STs on the QTP from 1980 to 2017 were investigated using Sen's slope estimator and the Mann-Kendall test. There was an increasing trend of ST in the deeper soil layer, which was less than that of the shallow soil layers in the spring and summer as well as annually. In contrast, the first-layer ST warming rate was significantly lower than that of the deeper soil layers in the autumn and winter. The significantly (P < 0.01) increasing trend of the annual ST indicates that the QTP has experienced climate warming during the past 38 years, which is one of the factors promoting permafrost degradation of the QTP.