The radiative forcing of black carbon (BC) is subject to many complex, interconnected sources of uncertainty. Here we isolate the role of the refractive index, which determines the extent to which BC absorbs and scatters radiation. We compare four refractive index schemes: three that are commonly used in Earth system models and a fourth more recent estimate with higher absorption. With other parameterizations held constant, changing BC's spectrally varying refractive index from the least- to most-absorbing estimate commonly used in Earth system models (m550nm=1.75-0.44i to m550nm=1.95-0.79i) increases simulated absorbing aerosol optical depth (AAOD) by 42 % and the effective radiative forcing from BC-radiation interactions (BC ERFari) by 47 %. The more recent estimate, m532nm=1.48-0.84i, increases AAOD and BC ERFari by 59 % and 100 % respectively relative to the low-absorption case. The AAOD increases are comparable to those from recent updates to aerosol emission inventories and, in BC source regions, up to two-thirds as large as the difference in AAOD retrieved from MISR (Multi-angle Imaging SpectroRadiometer) and POLDER-GRASP (Polarization and Directionality of the Earth's Reflectances instrument with the Generalized Retrieval of Atmosphere and Surface Properties algorithm) satellites. The BC ERFari increases are comparable to previous assessments of overall uncertainties in BC ERFari, even though this source of uncertainty is typically overlooked. Although model sensitivity to the choice of BC refractive index is known to be modulated by other parameterization choices, our results highlight the importance of considering refractive index diversity in model intercomparison projects.

Brown carbon (BrC) is a fraction of organic aerosol (OA) that absorbs radiation in the ultraviolet and short visible wavelengths. Its contribution to radiative forcing is uncertain due to limited knowledge of its imaginary refractive index (k). This study investigates the variability of k for OA from wildfires, residential, shipping, and traffic emission sources over Europe. The Multiscale Online Nonhydrostatic Atmosphere Chemistry (MONARCH) model simulated OA concentrations and source contributions, feeding an offline optical tool to constrain k values at 370 nm. The model was evaluated against OA mass concentrations from aerosol chemical speciation monitors (ACSMs) and filter sample measurements, as well as aerosol light absorption measurements at 370 nm derived from an Aethalometer (TM) from 12 sites across Europe. Results show that MONARCH captures the OA temporal variability across environments (regional, suburban, and urban background). Residential emissions are a major OA source in colder months, while secondary organic aerosol (SOA) dominates in warmer periods. Traffic is a minor primary OA contributor. Biomass and coal combustion significantly influence OA absorption, with shipping emissions also notable near harbors. Optimizing k values at 370 nm revealed significant variability in OA light absorption, influenced by emission sources and environmental conditions. Derived k values for biomass burning (0.03 to 0.13), residential (0.008 to 0.13), shipping (0.005 to 0.08), and traffic (0.005 to 0.07) sources improved model representation of OA absorption compared to a constant k. Introducing such emission source-specific constraints is an innovative approach to enhance OA absorption in atmospheric models.

The rapid warming of the Arctic, driven by glacial and sea ice melt, poses significant challenges to Earth's climate, ecosystems, and economy. Recent evidence indicates that the snow-darkening effect (SDE), caused by black carbon (BC) deposition, plays a crucial role in accelerated warming. However, high-resolution simulations assessing the impacts from the properties of snowpack and land-atmosphere interactions on the changes in the surface energy balance of the Arctic caused by BC remain scarce. This study integrates the Snow, Ice, and Aerosol Radiative (SNICAR) model with a polar-optimized version of the Weather Research and Forecasting model (Polar-WRF) to evaluate the impacts of snow melting and land-atmosphere interaction processes on the SDE due to BC deposition. The simulation results indicate that BC deposition can directly affect the surface energy balance by decreasing snow albedo and its corresponding radiative forcing (RF). On average, BC deposition at 50 ngg-1 causes a daily average RF of 1.6 Wm-2 in offline simulations (without surface feedbacks) and 1.4 Wm-2 in online simulations (with surface feedback). The reduction in snow albedo induced by BC is strongly dependent on snow depth, with a significant linear relationship observed when snow depth is shallow. In regions with deep snowpack, such as Greenland, BC deposition leads to a 25 %-41 % greater SDE impact and a 19 %-40 % increase in snowmelt compared to in areas with shallow snow. Snowmelt and land-atmosphere interactions play significant roles in assessing changes in the surface energy balance caused by BC deposition based on a comparison of results from offline and online coupled simulations via Polar-WRF and the community Noah land surface model (LSM) with multiple parameterization options (Noah-MP) and SNICAR. Offline simulations tend to overestimate SDE impacts by more than 50 % because crucial surface feedback processes are excluded. This study underscores the importance of incorporating detailed physical processes in high-resolution models to improve our understanding of the role of the SDE in Arctic climate change.

In South Asia, biomass is burned for energy and waste disposal, producing brown carbon (BrC) aerosols whose climatic impacts are highly uncertain. To assess these impacts, a real-world understanding of BrC's physio-optical properties is essential. For this region, the order-of-magnitude variability in BrC's spectral refractive index as a function of particle volatility distribution is poorly understood. This leads to oversimplified model parameterization and subsequent uncertainty in regional radiative forcing. Here we used the field-collected aerosol samples from major anthropogenic biomass activities to examine the methanol-soluble BrC optical properties. We show a strong relation between the absorption strength, wavelength dependence, and thermo-optical fractions of carbonaceous aerosols. Our observations show strongly absorbing BrC near the Himalayan foothills that may accelerate glacier melt, further highlighting the limitations of climate models where variable BrC properties are not considered. These findings provide crucial inputs for refining climate models and developing effective regional strategies to mitigate BrC emissions.

Aerosol absorption of visible light has an important impact on global radiative forcing. Wildfires are one of the major sources of light-absorbing aerosol, but there remains significant uncertainty about the magnitude, wavelength dependence, and bleaching of absorption from biomass burning aerosol. We collected and analyzed data from 21 western US wildfire smoke plumes during the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption and Nitrogen (WE-CAN) airborne measurement campaign to determine the contribution of black carbon (BC), brown carbon (BrC), and lensing to the aerosol mass absorption cross (MAC). Comparison to commonly used parameterizations and modeling studies suggests that model overestimation of absorption is likely due to incorrect BrC refractive indices. Modelers (Wang et al., 2018; Carter et al., 2021) invoke a bleaching process that decreases the MAC of organic aerosol (OA) to offset the overestimation of absorption in models. However, no evidence of a decreasing MAC is observed in individual WE-CAN fire plumes or in aged plumes from multiple fires. A decrease in OA mass and water-soluble organic carbon (WSOC), both normalized by carbon monoxide (CO) to correct for dilution, is observed with an increasing oxygen-to-carbon (O : C) ratio and a decreasing gas-phase toluene : benzene ratio, when data from all fires are combined in half of the individual fire plumes. This results in a strong decrease in total absorption at 405 nm and a slight decrease at 660 nm with these chemical markers. These results demonstrate that changes in absorption with chemical markers of plume age are the result of decreasing OA rather than changes in the MAC of the organic material itself. While decreasing MAC or OA mass with aging could both be called bleaching and can both correct overestimation of absorption in models, it is important to distinguish between these two effects because decreasing OA mass will also decrease scattering, which will cause a significantly different net radiative effect. We also find that an average of 54 % of non-BC absorption (23 % total absorption) at 660 nm is from water-soluble BrC, confirming that BrC absorption is important across the visible spectrum. Quantification of significant BrC at red wavelengths and observation of bleaching being caused by changes in OA with O : C and toluene : benzene markers of plume age provide important improvements to our understanding of BrC and critical constraints on aerosol absorption in regional and global climate models.

The Tibetan Plateau is a global hotspot of stratospheric intrusion, and elevated surface ozone was observed at ground monitoring sites. Still, links between the variability of surface ozone and stratospheric intrusion at the regional scale remain unclear. This study synthesized ground measurements of surface ozone over the Tibetan Plateau and analyzed their seasonal variations. The monthly mean surface ozone concentrations over the Tibetan Plateau peaked earlier in the south in April and May and later in the north in June and July. The migration of monthly surface ozone peaks was coupled with the synchronous movement of tropopause folds and the westerly jet that created conditions conducive to stratospheric ozone intrusion. Stratospheric ozone intrusion significantly contributed to surface ozone across the Tibetan Plateau, especially in the areas with high surface ozone concentrations during their peak-value month. We demonstrated that monthly variation of surface ozone over the Tibetan Plateau is mainly controlled by stratospheric intrusion, which warrants proper consideration in understanding the atmospheric chemistry and the impacts of ozone over this highland region and beyond.

Wildfires and agricultural burning generate seemingly increasing smoke aerosol emissions, impacting societal and natural ecosystems. To understand smoke's effects on climate and public health, we analyzed the spatiotemporal distribution of smoke aerosols, focusing on two major light-absorbing components, namely black carbon (BC) and brown carbon (BrC) aerosols. Using NASA's Earth Polychromatic Imaging Camera (EPIC) instrument aboard NOAA's Deep Space Climate Observatory (DSCOVR) spacecraft, we inferred BC and BrC volume fractions and particle mass concentrations based on spectral absorption provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm with 1-2 h temporal resolution and similar to 10 km spatial resolution over North America and central Africa. Our analyses of regional smoke properties reveal distinct characteristics for aerosol optical depth (AOD) at 443 nm, spectral single-scattering albedo (SSA), aerosol layer height (ALH), and BC and BrC amounts. Smoke aerosols in North America showed extremely high AOD up to 6, with elevated ALH (6-7 km) and significant BrC components up to 250 mg m-2 along the transport paths, whereas the smoke aerosols in central Africa exhibited stronger light absorption (i.e., lower SSA) and lower AOD, resulting in higher-BC mass concentrations and similar BrC mass concentrations than the cases in North America. Seasonal burning source locations in central Africa, following the seasonal shift in the Intertropical Convergence Zone and diurnal variations in smoke amounts, were also captured. A comparison of retrieved AOD443, SSA443, SSA680, and ALH with collocated AERONET and CALIOP measurements shows agreement with RMSE values of 0.2, 0.03-0.04, 0.02-0.04, and 0.8-1.3 km, respectively. An analysis of the spatiotemporal average reveals distinct geographical characteristics in smoke properties closely linked to burning types and meteorological conditions. Forest wildfires over western North America generated smoke with a small-BC volume fraction of 0.011 and a high ALH with large variability (2.2 +/- 1.2 km), whereas smoke from wildfires and agricultural burning over Mexico region shows more absorption and low ALH. Smoke from savanna fires over central Africa had the most absorption, with a high-BC volume fraction (0.015) and low ALH with a small variation (1.8 +/- 0.6 km) among the analyzed regions. Tropical forest smoke was less absorbing and had a high variance in ALH. We also quantify the estimation uncertainties related to the assumptions of BC and BrC refractive indices. The MAIAC EPIC smoke properties with BC and BrC volume and mass fractions and assessment of the layer height provide observational constraints for radiative forcing modeling and air quality and health studies.

Light-absorbing carbonaceous aerosols are important contributors to both air pollution and radiative forcing. However, their abundances and sources remain poorly constrained, as can be seen from the frequently identified discrepancies between the observed and modeled results. In this study, we focused on elemental carbon (EC; as a measure of black carbon) and light-absorbing organic carbon (i.e., BrC) in Northeast China, a new targeted region of the latest clean-air actions in China. Three campaigns were conducted during 2018-2021 in Harbin, covering distinct meteorological conditions and emission features. Various analytical methods were first evaluated, and the mass concentrations of both BrC and EC were validated. The validated BrC and EC measurement results were then used for source apportionment, together with other species including tracers (e.g., levoglucosan). The observation-based results suggested that despite the frigid winter in Harbin, the formation of secondary organic carbon (SOC) was enhanced at high levels of relative humidity (RH). This enhancement could also be captured by an air quality model incorporating heterogeneous chemistry. However, the model failed to reproduce the observed abundances of SOC, with significant underestimations regardless of RH levels. In addition, agricultural fires effectively increased the observation-based primary organic carbon (POC) concentrations and POC to EC ratios. Such roles of agricultural fires were not captured by the model, pointing to substantial underestimation of open burning emissions by the inventory. This problem merits particular attention for Northeast China, given its massive agricultural sector.

It is necessary to accurately determine the optical properties of highly absorbing black carbon (BC) aerosols to estimate their climate impact. In the past, there has been hesitation about using realistic fractal morphologies when simulating BC optical properties due to the complexity involved in the simulations and the cost of the computations. In this work, we demonstrate that, by using a benchmark machine learning (ML) algorithm, it is possible to make fast and highly accurate predictions of the optical properties for BC fractal aggregates. The mean absolute errors (MAEs) for the optical efficiencies ranged between 0.002 and 0.004, whereas they ranged between 0.003 and 0.004 for the asymmetry parameter. Unlike the computationally intensive simulations of complex scattering models, the ML-based approach accurately predicts optical properties in a fraction of a second. Physiochemical properties of BC, such as total particle size (number of primary particles (Npp), outer volume equivalent radius (ro), mobility diameter (Dm), outer primary particle size (ao), fractal dimension (Df), wavelength (lambda), and fraction of coating (fcoating), were used as input parameters for the developed ML algorithm. An extensive evaluation procedure was carried out in this study while training the ML algorithms. The ML-based algorithm compared well with observations from laboratory-generated soot, demonstrating how realistic morphologies of BC can improve their optical properties. Predictions of optical properties like single-scattering albedo (omega) and mass absorption cross- (MAC) were improved compared to the conventional Mie-based predictions. The results indicate that it is possible to generate optical properties in the visible spectrum using BC fractal aggregates with any desired physicochemical properties within the range of the training dataset, such as size, morphology, or organic coating. Based on these findings, climate models can improve their radiative forcing estimates using such comprehensive parameterizations for the optical properties of BC based on their aging stages.

Anthropogenic aerosols play a major role in the Earth-atmosphere system by influencing the Earth's radiative budget and precipitation and consequently the climate. The perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF). In this work, the present-day shortwave (SW), longwave (LW), and total (i.e., SW plus LW) ERF of anthropogenic aerosols is quantified using two different sets of experiments with prescribed sea surface temperatures (SSTs) from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6): (a) time-slice pre-industrial perturbation simulations with fixed SSTs (piClim) and (b) transient historical simulations with time-evolving SSTs (histSST) over the historical period (1850-2014). ERF is decomposed into three components for both piClim and histSST experiments: (a) ERFARI, representing aerosol-radiation interactions; (b) ERFACI, accounting for aerosol-cloud interactions (including the semi-direct effect); and (c) ERFALB, which is due to temperature, humidity, and surface albedo changes caused by anthropogenic aerosols. We present spatial patterns at the top-of-atmosphere (TOA) and global weighted field means along with inter-model variability (1 standard deviation) for all SW, LW, and total ERF components (ERFARI, ERFACI, and ERFALB) and for every experiment used in this study. Moreover, the inter-model agreement and the robustness of our results are assessed using a comprehensive method as utilized in the IPCC Sixth Assessment Report. Based on piClim experiments, the total present-day (2014) ERF from anthropogenic aerosol and precursor emissions is estimated to be -1.11 +/- 0.26 Wm-2, mostly due to the large contribution of ERFACI to the global mean and to the inter-model variability. Based on the histSST experiments for the present-day period (1995-2014), similar results are derived, with a global mean total aerosol ERF of -1.28 +/- 0.37 Wm-2 and dominating contributions from ERFACI. The spatial patterns for total ERF and its components are similar in both the piClim and histSST experiments. Furthermore, implementing a novel approach to determine geographically the driving factor of ERF, we show that ERFACI dominates over the largest part of the Earth and that ERFALB dominates mainly over the poles, while ERFARI dominates over certain reflective surfaces. Analysis of the inter-model variability in total aerosol ERF shows that SW ERFACI is the main source of uncertainty predominantly over land regions with significant changes in aerosol optical depth (AOD), with eastern Asia contributing mostly to the inter-model spread of both ERFARI and ERFACI. The global spatial patterns of total ERF and its components from individual aerosol species, such as sulfates, organic carbon (OC), and black carbon (BC), are also calculated based on piClim experiments. The total ERF caused by sulfates (piClim-SO2) is estimated at -1.11 +/- 0.31 Wm-2, and the OC ERF (piClim-OC) is -0.35 +/- 0.21 Wm-2, while the ERF due to BC (piClim-BC) is 0.19 +/- 0.18 Wm-2. For sulfates and OC perturbation experiments, ERFACI dominates over the globe, whereas for BC perturbation experiments ERFARI dominates over land in the Northern Hemisphere and especially in the Arctic. Generally, sulfates dominate ERF spatial patterns, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere (NH), such as North America, Europe, and eastern and southern Asia. Our analysis of the temporal evolution of ERF over the historical period (1850-2014) reveals that ERFACI clearly dominates over ERFARI and ERFALB for driving the total ERF temporal evolution. Moreover, since the mid-1980s, total ERF has become less negative over eastern North America and western and central Europe, while over eastern and southern Asia there is a steady increase in ERF magnitude towards more negative values until 2014.