Aerosol Absorption Optical Depth Research Articles

Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China

Machine learning methods have been recognized as rapid methods for satellite-based aerosol retrievals but have not been widely applied in geostationary satellites. In this study, we developed a wide and deep learning model to retrieve the aerosol optical depth (AOD) using Himawari-8. Compared to traditional deep learning methods, we embedded a “wide” modeling component and tested the proposed model across China using independent training (2016–2018) and test (2019) datasets. The results showed that the “wide” model improves the accuracy and enhances model interpretability. The estimates exhibited better accuracy (R2 = 0.81, root-mean-square errors (RMSEs) = 0.19, and within the estimated error (EE) = 63%) than those of the deep-only models (R2 = 0.78, RMSE = 0.21, within the EE = 58%). In comparison with extreme gradient boosting (XGBoost) and Himawari-8 V2.1 AOD products, there were also significant improvements. In addition to higher accuracy, the interpretability of the proposed model was superior to that of the deep-only model. Compared with other seasons, higher contributions of spring to the AOD concentrations were interpreted. Based on the application of the wide and deep learning model, the near-real-time variation of the AOD over China could be captured with an ultrafine temporal resolution.

Direct radiative forcing of light-absorbing carbonaceous aerosols in China

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.

Measurement report: Assessing the impacts of emission uncertainty on aerosol optical properties and radiative forcing from biomass burning in peninsular Southeast Asia

Abstract. Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg M−1), with 1.09 ± 0.83 Tg M−1 and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD > 1) regions range from 15–22.5∘ N, 97–110∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of −32.60 ± 24.50 W m−2 at the surface, positive forcing (1.70 ± 1.40 W m−2) in the atmosphere, and negative forcing (−30.89 ± 23.6 W m−2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region.

Quantifying the effects of the microphysical properties of black carbon on the determination of brown carbon using measurements at multiple wavelengths

Abstract. Methods based on the absorption Ångström exponent (AAE) are widely used to estimate the absorption by brown carbon (BrC), and the estimated absorption by BrC can be significantly different from 0, even for pure black carbon (BC). However, few studies have systematically quantified the effects of BC microphysical properties. Moreover, the conditions under which AAE-based methods are applicable are still unclear. In this work, we used BC models partially coated with non-absorbing materials to calculate the total absorption. Since the total absorption is entirely due to BC, the estimated BrC absorption should be 0 if the retrieval methods are accurate. Thus, the ratio of the estimated BrC absorption to BC absorption (ABSBrC) should be the proportion of the BC absorption that is incorrectly attributed to BrC. The results show that a BC AAE of 1 can generally provide reasonable estimates for freshly emitted BC, since ABSBrC is generally in the range of −4.8 % to 2.7 % during that period. However, when BC aerosols are aged, ABSBrC can sometimes reach about 38.7 %. The wavelength dependence of the AAE (WDA) method does not necessarily improve the estimates; sometimes a negative ABSBrC of about −40.8 % is found for partially coated BC. By combining simulations of a global chemical transport model, this work also quantified the effects of BC microphysical properties on BrC global aerosol absorption optical depth (AAOD) estimates. The AAE = 1 method sometimes leads to a misassigned global mean AAOD of about −0.43–0.46×10-3 if the BC aerosols have a complex morphology. The WDA method does not necessarily improve the estimates. In our cases, the WDA methods based on spherical models could lead to a global-mean misassigned AAOD range of about −0.87–0.04×10-3. At the regional scale, the AAE = 1 method sometimes leads to a distributed AAOD of about −7.3 to 5.7×10-3 in some specific regions. Mie-theory-based WDA methods lead to an estimated AAOD error of about -22×10-3 in some regions (e.g., East Asia). This work also showed that the misattributed BrC absorption would lead to substantial uncertainties in the estimation of the global direct radiative forcing (DRF) of absorbing aerosols from different sources.

Threefold reduction of modeled uncertainty in direct radiative effects over biomass burning regions by constraining absorbing aerosols.

Absorbing aerosols emitted from biomass burning (BB) greatly affect the radiation balance, cloudiness, and circulation over tropical regions. Assessments of these impacts rely heavily on the modeled aerosol absorption from poorly constrained global models and thus exhibit large uncertainties. By combining the AeroCom model ensemble with satellite and in situ observations, we provide constraints on the aerosol absorption optical depth (AAOD) over the Amazon and Africa. Our approach enables identification of error contributions from emission, lifetime, and MAC (mass absorption coefficient) per model, with MAC and emission dominating the AAOD errors over Amazon and Africa, respectively. In addition to primary emissions, our analysis suggests substantial formation of secondary organic aerosols over the Amazon but not over Africa. Furthermore, we find that differences in direct aerosol radiative effects between models decrease by threefold over the BB source and outflow regions after correcting the identified errors. This highlights the potential to greatly reduce the uncertainty in the most uncertain radiative forcing agent.

Aerosol absorption using in situ filter-based photometers and ground-based sun photometry in the Po Valley urban atmosphere

Abstract. Light-absorbing aerosols (LAAs) are short-lived climate forcers with a significant impact on Earth's radiative balance. LAAs include dust aerosols, black carbon (BC) and organic light-absorbing carbonaceous aerosol (collectively termed brown carbon, BrC), which have also been proven to be highly toxic. In this study, aerosol absorption at five wavelengths (ranging from ultraviolet to infrared) was monitored continuously using filter-based photometers during two winter seasons in 2020 and 2021 in the city of Modena (southern central Po Valley, northern Italy), at two regulatory air quality monitoring sites, along with other pollutants (coarse particulate matter, PM10; fine particulate matter, PM2.5; O3; NO; NO2; and C6H6) and the vehicular traffic rate. The aerosol optical depth (AOD) and other column aerosol optical properties were concurrently monitored at four wavelengths by an AErosol RObotic NETwork (AERONET) sun photometer under urban background conditions within Modena. In situ absorption levels were apportioned to both sources (fossil fuel and biomass burning) and species (BC and BrC), while columnar absorption was apportioned to BC, BrC and mineral dust. The combined analysis of the atmospheric aerosol and gas measurements and of the meteorological conditions (in situ and from the ERA5 reanalysis) identified the location of potential urban sources of BC and BrC, most likely related to traffic and biomass burning. In situ data show different diurnal/weekly patterns for BrC from biomass burning and BC from traffic, with minor differences between the background and the urban traffic conditions. AERONET version 3 absorption aerosol optical depth (AAOD) retrievals at four wavelengths allowed the estimation of the absorptive direct radiative effect due to LAAs over the same period under the reasonable assumption that the AOD signal is concentrated within the mixing layer. AERONET retrievals showed a modest correlation of columnar absorption with planetary boundary layer (PBL)-scaled in situ observations, although the correlation improved significantly during a desert dust transport event that affected both in situ aerosol and columnar absorption, particularly in the blue spectrum range. A low correlation occurred between the contribution of BrC to aerosol absorption for the in situ and the columnar observations, with the BrC contribution being generally larger for in situ observations. Finally, evidence of a highly layered atmosphere during the study period, featuring significant spatial mixing and modest vertical mixing, was shown by ERA5-based atmospheric temperature profiles and by the large correlation of concurrent AERONET AOD retrievals in Modena and in Ispra (on the northwestern side of the Po Valley, ca. 225 km from Modena).

An AERONET-based methodology to retrieve black carbon light absorption and comparison with MERRA-2 data

The contribution of black carbon in absorption aerosol optical depth (BC AAOD) can be retrieved using depolarization ratio (DPR, δp), single scattering albedo (SSA, ω), and Ångstrom exponent (AE, å). AErosol RObotic NETwork (AERONET) inversion products provide ground-based long-term observations of aerosol optical properties based on the sun photometer's observations. In this study, the AERONET version 3 level 2.0 products are utilized to approximate BC AAOD on a global scale during the recent two decades (2000–2018). We compared our AERONET-retrieved BC AAODs with the ones provided by the Modern-Era Retrospective analysis for Research and Applications, version 2.0 (MERRA-2) data, at the selected AERONET site's location and observation time. We found the highest MERRA-2 and AERONET-derived BC AAOD over densely populated countries such as China and India. Further, Nigeria, one of the largest sources of biomass burning and a leading gas-flaring country, showed increased values of BC AAOD. Both datasets confirmed a drop in BC AAOD over Sao-Paulo, Beijing, and Seoul from 2000 to 2018. AERONET and MERRA-2 data indicated higher BC variations during cold months in Beijing, Kanpur, Seoul, Ilorin, and Sao-Paulo. We concluded that the high BC values over the populous countries mainly owe to the considerable BC emission from transportation, industrial, and residential sectors in response to the high population. A comparison of MERRA-2 and our AERONET-derived retrieval methodology suggested lower values of MERRA-2 BC AAOD compared to AERONET-derived variations in Sao-Paulo.

A Dissection of the Inter‐Model Spread of the Aerosol Direct Radiative Effect in CMIP6 Models

AbstractThe all‐sky Aerosol Direct Radiative Effect (ADRE) varies considerably among global climate models (GCMs), which results from differences in aerosol and atmospheric states and ADRE sensitivity to aerosol‐related radiative processes. This study uses a regression method to analyze the inter‐model spread of ADRE among the GCMs of the Sixth Coupled Model Intercomparison Projects (CMIP6). The key state variables examined include scattering and absorbing aerosol optical depth, surface albedo, and shortwave cloud radiative effect. We find that differences in state variables and radiative sensitivity explain 67% and 17%, respectively, of the global ADRE anomaly. The ADRE anomaly in different models is dominated by different factors, which sometimes leads to compensating effects. For the global mean ADRE anomaly, aerosol optical depth differences dominate in CNRM‐ESM2‐1 and GFDL‐ESM4 models, while ADRE sensitivity variations to aerosol‐only scattering effect dominate in HadGEM3‐GC31‐LL, MPI‐ESM‐1‐2‐HAM, and MRI‐ESM2‐0 models.

An Aerosol Optical Module With Observation‐Constrained Black Carbon Properties for Global Climate Models

AbstractAtmospheric black carbon (BC) aerosols have been long‐lasting uncertain components in environmental and climate studies. Global climate models (GCMs) potentially overestimate BC absorption efficiency due to a lack of consideration of complex BC microphysical and mixing properties. We extract multiple BC properties from observations and develop an aerosol optical module known as Advanced Black Carbon (ABC) in the framework of the Modal Aerosol Model version 4 (MAM4). The ABC module is implemented in the Community Atmosphere Model version 6 (CAM6) and evaluated by in situ and remote sensing observations. CAM6‐ABC addresses the shortcomings of CAM6‐MAM4 in terms of BC microphysical and mixing properties, particularly their size, mixing state and optical simulations. Sensitivity simulations show that the global BC absorption aerosol optical depth at 550 nm simulated by CAM6‐ABC is reduced by ∼29% compared with that in CAM6‐MAM4. The BC absorption enhancement simulated by CAM6‐ABC is reduced from ∼2.6 of the default MAM4 to ∼1.4, which is closer to the observed values (mostly less than 1.5). With improved BC absorption estimation, the biases of aerosol single‐scattering coalbedo simulations are reduced by 18%–69% compared with global Aerosol Robotic Network observations. Moreover, the globally averaged BC direct radiative effect is reduced from 0.37 to 0.28 W/m2 at the top of the atmosphere. Our new scheme alleviates the overestimation of BC absorption in GCMs by constraining BC microphysical and mixing properties when assessing aerosol radiative and climate effects, and it can be easily implemented in most modal‐based aerosol modules of climate models.

A Plant Species Dependent Wildfire Black Carbon Emission Inventory in Northern Eurasia

AbstractWildfire emission inventories are usually applied with biome‐scale emission factors for atmospheric modeling. However, emission factors measured for different plant species vary substantially within the same biome. We apply the species‐specific emission factors and refine the Fire Emission Inventory‐northern Eurasia (FEI‐NE), and derive the wildfire black carbon emission inventory in northern Eurasia from 2002 to 2015. Our new inventory produces 61% more black carbon emissions than current estimates based on Global Fire Emission Database (GFED) and 33% less than FEI‐NE. Model simulations with different inventories are compared with ground‐based and satellite retrievals of aerosol absorption optical depth (AAOD). Compared with the Ozone Monitoring Instrument, the normalized root mean square deviation of AAOD over northern Eurasia is reduced from 1.0 under FEI‐NE to 0.95 through application of the new inventory. This study reveals the importance of applying sub‐biome‐scale emission factors for wildfire inventories development and revisiting emissions uncertainty in atmospheric modeling.

Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations

Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development.

Assimilation of POLDER observations to estimate aerosol emissions

Abstract. We apply a local ensemble transform Kalman smoother (LETKS) in combination with the global aerosol–climate model ECHAM–HAM to estimate aerosol emissions from POLDER-3/PARASOL (POLarization and Directionality of the Earth's Reflectances) observations for the year 2006. We assimilate aerosol optical depth at 550 mnm (AOD550), the Ångström exponent at 550 and 865 nm (AE550–865), and single-scattering albedo at 550 nm (SSA550) in order to improve modeled aerosol mass, size and absorption simultaneously. The new global aerosol emissions increase to 1419 Tg yr−1 (+28 %) for dust, 1850 Tg yr−1 (+75 %) for sea salt, 215 Tg yr−1 (+143 %) for organic aerosol and 13.3 Tg yr−1 (+75 %) for black carbon, while the sulfur dioxide emissions increase to 198 Tg yr−1 (+42 %) and the total deposition of sulfates to 293 Tg yr−1 (+39 %). Organic and black carbon emissions are much higher than their prior values from bottom-up inventories, with a stronger increase in biomass burning sources (+193 % and +90 %) than in anthropogenic sources (115 % and 70 %). The evaluation of the experiments with POLDER (assimilated) and AERONET as well as MODIS Dark Target (independent) observations shows a clear improvement compared with the ECHAM–HAM control run. Specifically based on AERONET, the global mean error in AOD550 improves from −0.094 to −0.006, while absorption aerosol optical depth at 550 nm (AAOD550) improves from −0.009 to −0.004 after the assimilation. A smaller improvement is also observed in the AE550–865 mean absolute error (from 0.428 to 0.393), with a considerably higher improvement over isolated island sites at the ocean. The new dust emissions are closer to the ensemble median of AEROCOM I, AEROCOM III and CMIP5 as well as some of the previous assimilation studies. The new sea salt emissions have become closer to the reported emissions from previous studies. Indications of a missing fraction of coarse dust and sea salt particles are discussed. The biomass burning changes (based on POLDER) can be used as alternative biomass burning scaling factors for the Global Fire Assimilation System (GFAS) inventory distinctively estimated for organic carbon (2.93) and black carbon (1.90) instead of the recommended scaling of 3.4 (Kaiser et al., 2012). The estimated emissions are highly sensitive to the relative humidity due to aerosol water uptake, especially in the case of sulfates. We found that ECHAM–HAM, like most of the global climate models (GCMs) that participated in AEROCOM and CMIP6, overestimated the relative humidity compared with ERA5 and as a result the water uptake by aerosols, assuming the kappa values are not underestimated. If we use the ERA5 relative humidity, sulfate emissions must be further increased, as modeled sulfate AOD is lowered. Specifically, over East Asia, the lower AOD can be attributed to the underestimated precipitation and the lack of simulated nitrates in the model.

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.

Absorbing Aerosol Optical Properties and Radiative Effects on Near-Surface Photochemistry in East Asia

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[O1D]) 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[O1D]) 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.

Observations suggest that North African dust absorbs less solar radiation than models estimate

Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects.

Exploring the Spatiotemporal Variation in Light-Absorbing Aerosols and Its Relationship with Meteorology over the Hindukush–Himalaya–Karakoram Region

Light-absorbing aerosols such as black carbon (BC), organic carbon (OC), and dust can cause the warming and melting of glaciers by absorbing sunlight. Further research is needed to understand the impact of light-absorbing aerosols on the Hindukush–Karakoram–Himalaya region in northern Pakistan. Therefore, spatiotemporal variation in absorbing surface mass concentration retrieved from Modern-Era Retrospective analysis for Research and Applications, optical properties such as aerosol optical depth (AOD) and absorption aerosol optical depth (AAOD) from the ozone monitoring instrument, and meteorological parameters from the European Centre for Medium-Range Weather Forecasts Reanalysis were investigated over northern Pakistan from 2001 to 2021. The BC concentration was lowest in May and highest in November, having a seasonal maximum peak in winter (0.31 ± 0.04 µg/m3) and minimum peak in spring (0.17 ± 0.01 µg/m3). In addition, OC concentration was found to be greater in November and smaller in April, with a seasonal higher peak in autumn (1.32 ± 0.32 µg/m3) and a lower peak in spring (0.73 ± 0.08 µg/m3). The monthly and seasonal variabilities in BC and OC concentrations are attributed to solid fuels, biomass burning, changes in vegetation, agricultural activities, and meteorology. In contrast, the dust concentration was high in July and low in December, with a seasonal average high concentration in summer (44 ± 9 µg/m3) and low concentration in winter (13 ± 2 µg/m3) due to drier conditions, dust activity, long-range transport, and human activities. Moreover, the seasonal variation in AOD and AAOD was identical and higher in the summer and lower in the winter due to dust aerosol loading and frequent dust activities. AOD and AAOD followed a similar pattern of spatial variation over the study area. Meteorological parameters greatly impact light-absorbing aerosols; therefore, low temperatures in winter increase BC and OC concentrations due to shallow boundary layers, while severe precipitation in spring decreases concentrations. During summer, dry conditions cause soil erosion and increase the amount of dust suspended in the atmosphere, leading to higher AOD and AAOD values. Conversely, higher precipitation rates and speedy winds disperse the dust aerosols in winter, resulting in lower AOD and AAOD values.

A study on optical properties, classification, and transport of aerosols during the smog period over South Asia using remote sensing.

Over the past few years, South Asian region has experienced frequent and thick smog events because of rapid population growth and enhanced anthropogenic activities, particularly in the Indo-Gangetic Plain (IGP). Therefore, the present study investigates aerosol properties such as aerosol optical depth (AOD) (500nm), Angstrom exponent (AE) (440-870nm), single scattering albedo (SSA), fine-mode fraction (FMF), absorption aerosol optical depth (AAOD), and absorption aerosol exponent (AAE) over selected AERONET sites namely Bhola (2012-2021), Dhaka (2012-2021), Jaipur (2011-2021), Kanpur (2011-2021), Karachi (2011-2021), Lahore (2011-2021), and Pokhara (2011-2021) in the IGP during the smog period (October, November, and December). Additionally, different aerosol types were categorized using AERONET direct sun (AOD, AE) and inversion products (VSD, SSA, RI, FMF, and ASY). The monthly mean AOD, AE, and FMF varied from ⁓0.33 to 1.07, ⁓0.3 to 1.4, and 0.6-0.9µm over all selected AERONET sites during the smog period. Moreover, the outcomes revealed the dominance of biomass-burning and urban/ industrial aerosols over Lahore, Karachi, Dhaka, and Bhola during the smog period. Contrary to this, dust and mixed aerosols were abundant over Jaipur and Karachi, respectively. Furthermore, HYSPLIT cluster analysis is used to trace the transmission paths and potential sources of aerosols over selected sites.

Absorbing Aerosol Optical Depth From OMI/TROPOMI Based on the GBRT Algorithm and AERONET Data in Asia

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.

Spatiotemporal analysis of absorbing aerosols and radiative forcing over environmentally distinct stations in East Africa during 2001–2018

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 characterizing 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 environmentally specific sites in EA. The annual mean absorption aerosol optical depth (AAOD440 nm), absorption Angstrom Exponent (AAE440−870 nm), total effective radius (REff), and total volume concentration (μm3/μm2) revealed significant spatial heterogeneity over the domain. The study domain exhibited a significant contribution of fine-mode aerosols compared to the coarse-mode particles. The monthly variation in SSA440 nm over EA explains the strength in absorption aerosols 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 ∼40 to ∼50 %, while weakly absorbing coarse-mode particles accounted for ∼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 indication of the role of aerosols in regional climate change. The study contributed to understanding aerosol absorption and radiative characteristics over EA and can form the basis of other related studies over the domain and beyond.

Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing

Quantitative estimations of atmospheric aerosol absorption are rather uncertain due to the lack of reliable information about the global distribution. Because the information about aerosol properties is commonly provided by single-viewing photometric satellite sensors that are not sensitive to aerosol absorption. Consequently, the uncertainty in aerosol radiative forcing remains one of the largest in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC AR5 and AR6). Here, we use multi-angular polarimeters (MAP) to provide constraints on emission of absorbing aerosol species and estimate global aerosol absorption optical depth (AAOD) and its climate effect. Our estimate of modern-era mid-visible AAOD is 0.0070 that is higher than IPCC by a factor of 1.3-1.8. The black carbon instantaneous direct radiative forcing (BC DRF) is +0.33 W/m2 [+0.17, +0.54]. The MAP constraint narrows the 95% confidence interval of BC DRF by a factor of 2 and boosts confidence in its spatial distribution.