Aerosol-radiation Interactions Research Articles

Unraveling the Mechanism of the Holes in the Blanket of Fog Over the Indo‐Gangetic Plains: Are They Driven by Urban Heat Islands or Aerosol?

AbstractFog holes were reported over cities of the Indo‐Gangetic plains of India, which were attributed to the urban heat island (UHI) effect. The present study reports the observational evidence of fog holes over rural area using satellite and ground observations. Delayed onset and early dissipation of fog is observed over the holes. Numerical simulations demonstrate that aerosol‐radiation interaction (ARI) leads to fog holes over both urban and rural regions. The anthropogenic aerosols and associated ARI dominate the UHI effect over the urban fog holes, while the aerosol absorption due to ARI mainly controls the rural fog holes. Turning off aerosol absorption causes ∼ 2 hours delay in the fog dissipation over urban area, whereas it yields persistent fog over rural area under saturated environment. An enhancement of soluble Aitken black carbon over the fog holes indicates the importance of aging process during fog dissipation.

Impact of aerosol-radiation interaction and heterogeneous chemistry on the winter decreasing PM2.5 and increasing O3 in Eastern China 2014–2020

In the context of the prevalent winter air quality issues in China marked by declining PM2.5 and rising O3, this study employed a modified WRF-Chem model to examine the aerosol radiation interaction (ARI), heterogeneous chemistry (AHC), and their combined impact (ALL) on the variations in O3 and PM2.5 during the 2014–2020 in eastern China. Our analysis confirmed that ARI curtailed O3 while elevating PM2.5. AHC reduced O3 through heterogeneous absorption of NOx and hydroxides while notably fostering fine-grained sulfate, resulting in a PM2.5 increase. Emission reductions mitigated the inhibitory impact of ARI on meteorological fields and photolysis rates. Emission reduction individually without aerosol feedback led to a 5.43 ppb O3 increase and a 22.89 µg/m3 PM2.5 decrease. ARI and AHC amplified the emission-reduction-induced (ERI) O3 rise by 1.83 and 0.31 ppb, respectively. The response of ARI to emission diminution brought about a modest PM2.5 increase of 0.31 µg/m3. Conversely, AHC, acting as the primary contributor, caused a noteworthy PM2.5 decrease of 4.60 µg/m3. As efforts concentrate on reducing PM2.5, the promotion of ARI on PM2.5 counterbalanced the efficacy of emission reduction and the AHC-induced strengthening of PM2.5 decrease. The ALL magnified the ERI O3 increase by 38.9% and PM2.5 decrease by 18.7%. Sensitivity experiments with different degrees of emission reduction demonstrated a consistent linear relationship between the ALL-induced enhancement of O3 increase and PM2.5 decrease to the ERI PM2.5 decline. Our investigation revealed the complex connection between emissions and aerosol feedback in influencing air quality.

Weakened aerosol–radiation interaction exacerbating ozone pollution in eastern China since China's clean air actions

Abstract. Since China's clean air action, PM2.5 (particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less) air quality has improved, while ozone (O3) pollution has become more severe. Here we apply a coupled meteorology–chemistry model (WRF-Chem: Weather Research and Forecasting model coupled to Chemistry v3.7.1) to quantify the responses of aerosol–radiation interaction (ARI) to anthropogenic emission reductions from 2013 to 2017, including aerosol–photolysis interaction (API) related to photolysis rate change and aerosol–radiation feedback (ARF) related to meteorological field change and their contributions to O3 increases over eastern China in summer and winter. Sensitivity experiments show that the decreased anthropogenic emissions play a more prominent role in the increased daily maximum 8 h average (MDA8) O3 in both summer (+1.96 ppb vs. +0.07 ppb) and winter (+3.56 ppb vs. −1.08 ppb) than the impacts of changed meteorological conditions in urban areas. The decreased PM2.5 caused by emission reductions can result in a weaker impact of ARI on O3 concentrations, which superimposes its effect on the worsened O3 air quality. The weakened ARI due to decreased anthropogenic emissions aggravates the summer (winter) O3 pollution by +0.81 ppb (+0.63 ppb), averaged over eastern China, with weakened API contributing 55.6 % (61.9 %) and ARF contributing 44.4 % (38.1 %), respectively. This superimposed effect is more significant for urban areas during summer (+1.77 ppb). Process analysis indicates that the enhanced chemical production is the dominant process for the increased O3 concentrations caused by weakened ARI in both summer and winter. This study innovatively reveals the adverse effect of weakened aerosol–radiation interaction due to decreased anthropogenic emissions on O3 air quality, indicating that more stringent coordinated air pollution control strategies should be implemented for significant improvements in future air quality.

Intercomparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1–CMAQ v5.3.1, WRF–Chem v4.1.1, and WRF v3.7.1–CHIMERE v2020r1) in eastern China

Abstract. Two-way coupled meteorology and air quality models, which account for aerosol–radiation–cloud interactions, have been employed to simulate meteorology and air quality more realistically. Although numerous related studies have been conducted, none have compared the performances of multiple two-way coupled models in simulating meteorology and air quality over eastern China. Thus, we systematically evaluated annual and seasonal meteorological and air quality variables simulated by three open-source, widely utilized two-way coupled models (Weather Research and Forecasting (WRF)–Community Multiscale Air Quality (WRF–CMAQ), WRF coupled with chemistry (WRF–Chem), and WRF coupled with a regional chemistry-transport model named CHIMERE (WRF–CHIMERE)) by validating their results with surface and satellite observations for eastern China in 2017. Although we have made every effort to evaluate these three coupled models by using configurations that are as consistent as possible, there are still unavoidable differences between them in their treatments of physical and chemical processes. Our thorough evaluations revealed that all three two-way coupled models captured the annual and seasonal spatiotemporal characteristics of meteorology and air quality reasonably well. Notably, the role of the aerosol–cloud interaction (ACI) in improving the models' performances was limited compared to that of the aerosol–radiation interaction (ARI). The sources of uncertainties and bias in the different ACI schemes in the two-way coupled models were identified. With sufficient computational resources, these models can provide more accurate air quality forecasting to support atmospheric environment management and deliver timely warnings of heavy air pollution events. Finally, we propose potential improvements to two-way coupled models for future research.

The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020

Abstract. A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for obtaining long-term in situ aerosol data due to its harsh environmental conditions. Here, we provide the more reliable new vertical aerosol index (AI) parameter from the spaceborne-based lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) for daytime and nighttime to investigate the aerosol's climatology over the TP region during 2007–2020. The calculated vertical AI was derived from the aerosol extinction coefficient (EC), which was rigorously quality-checked and validated for passive satellite sensors (MODIS) and ground-based lidar measurements. Generally, our results demonstrated that there was agreement of the AI dataset with the CALIOP and ground-based lidar. In addition, the results showed that, after removing the low-reliability aerosol target signal, the optimized data can obtain the aerosol characteristics with higher reliability. The data also reveal the patterns and concentrations of high-altitude vertical structure characteristics of the tropospheric aerosol over the TP. They will also help to update and make up the observational aerosol data in the TP. We encourage climate modelling groups to consider new analyses of the AI vertical patterns, comparing the more accurate datasets, with the potential to increase our understanding of the aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) and their climate effects. Data described in this work are available at https://doi.org/10.11888/Atmos.tpdc.300614 (Huang, 2023).

Effects of smoke on marine low clouds and radiation during 2020 western United States wildfires

Biomass burning aerosols (BBAs) influence the climate directly by scattering and absorbing sunlight and indirectly by changing the cloud properties through serving as cloud condensation nuclei (CCN) or ice-nucleating particles (INPs). Here we used the WRF-Chem model to simulate the transport of BBAs and their interactions with clouds and radiation during the western United States wildfires in September 2020. The simulated cloud and aerosol fields are comparable to the satellite observations from CALIPSO and MODIS. It is shown that smoke exerts negative radiative effects over both ocean and land. Over the nearly cloudless land, the negative radiative effect is caused by aerosols reflecting shortwave radiation. However, over the ocean covered by stratocumulus, aerosol-cloud interaction (ACI) induces a significant negative radiative effect (−25.6 W/m2 on average), because the reduction of droplet radius not only increases the brightness of clouds and prolongs their lifespan, but also cools their surroundings and increases relative humidity, which in turn increases cloud water content. On the contrary, aerosol-radiation interaction (ARI) leads to a positive radiative effect (+10.3 W/m2 on average) over the oceanic regions due to the absorption of sunlight reflected by low clouds and a slight decrease in cloud water. In our research, the counterclockwise vortex over the Northeast Pacific transports the smoke to remote regions and lifts the smoke to 4–8 km height. This results in a wide-ranging impact of the smoke on clouds and radiation, yet it diminishes the magnitude of ARI's effect on marine stratocumulus. Moreover, over ocean, ARI results in cooling at the cloud top and warming close to the sea surface, leading to a rise in marine stratocumulus height. These vertical atmospheric adjustments within the PBL differ from the reduced surface temperature with suppressed PBL over terrestrial regions.

Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution

Abstract. In accordance with progression in current capabilities towards high-resolution approaches, applying a convective-permitting resolution to global aerosol models helps comprehend how complex cloud–precipitation systems interact with aerosols. This study investigates the impacts of a double-moment bulk cloud microphysics scheme, i.e., NICAM Double-moment bulk Water 6 developed in this study (NDW6-G23), on the spatiotemporal distribution of aerosols in the Nonhydrostatic ICosahedral Atmospheric Model as part of the version-19 series (NICAM.19) with 14 km grid spacing. The mass concentrations and optical thickness of the NICAM-simulated aerosols are generally comparable to those obtained from in situ measurements. However, for some aerosol species, especially dust and sulfate, the differences between experiments of NDW6 and of the NICAM single-moment bulk module with six water categories (NSW6) were larger than those between experiments with different horizontal resolutions (14 and 56 km grid spacing), as shown in a previous study. The simulated aerosol burdens using NDW6 are generally lower than those using NSW6; the net instantaneous radiative forcing due to aerosol–radiation interaction (IRFari) is estimated to be −1.36 W m−2 (NDW6) and −1.62 W m−2 (NSW6) in the global annual mean values at the top of the atmosphere (TOA). The net effective radiative forcing due to anthropogenic aerosol–radiation interaction (ERFari) is estimated to be −0.19 W m−2 (NDW6) and −0.23 W m−2 (NSW6) in the global annual mean values at the TOA. This difference among the experiments using different cloud microphysics modules, i.e., 0.26 W m−2 or 16 % difference in IRFari values and 0.04 W m−2 or 16 % difference in ERFari values, is attributed to a different ratio of column precipitation to the sum of the column precipitation and column liquid cloud water, which strongly determines the magnitude of wet deposition in the simulated aerosols. Since the simulated ratios in the NDW6 experiment are larger than those of the NSW6 result, the scavenging effect of the simulated aerosols in the NDW6 experiment is larger than that in the NSW6 experiment. A large difference between the experiments is also found in the aerosol indirect effect (AIE), i.e., the net effective radiative forcing due to aerosol–cloud interaction (ERFaci) from the present to preindustrial days, which is estimated to be −1.28 W m−2 (NDW6) and −0.73 W m−2 (NSW6) in global annual mean values. The magnitude of the ERFaci value in the NDW6 experiment is larger than that in the NSW6 result due to the differences in both the Twomey effect and the susceptibility of the simulated cloud water to the simulated aerosols between NDW6 and NSW6. Therefore, this study shows the importance of the impacts of the cloud microphysics module on aerosol distributions through both aerosol wet deposition and the AIE.

Changes in global DMS production driven by increased CO2 levels and its impact on radiative forcing

Our study highlights the importance of understanding the future changes in dimethyl-sulfide (DMS), the largest natural sulfur source, in the context of ocean acidification driven by elevated CO2 levels. We found a strong negative correlation (R2 = 0.89) between the partial pressure of carbon dioxide (pCO2) and sea-surface DMS concentrations based on global observational datasets, not adequately captured by the Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth System Models (ESMs). Using this relationship, we refined projections of future sea-surface DMS concentrations in CMIP6 ESMs. Our study reveals a decrease in global sea-surface DMS concentrations and the associated aerosol radiative forcing compared to ESMs’ results. These reductions represent ~9.5% and 11.1% of the radiative forcings resulting from aerosol radiation and cloud interactions in 2100 reported by the Intergovernmental Panel on Climate Change Sixth Assessment Report. Thus, future climate projections should account for the climate implications of changes in DMS production due to ocean acidification.

Increased importance of aerosol–cloud interactions for surface PM2.5 pollution relative to aerosol–radiation interactions in China with the anthropogenic emission reductions

Abstract. Surface fine particulate matter (PM2.5) pollution can be enhanced by feedback processes induced by aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs). Many previous studies have reported enhanced PM2.5 concentrations induced by ARIs and ACIs for episodic events in China. However, few studies have examined the changes in the ARI- and ACI-induced PM2.5 enhancements over a long period, though the anthropogenic emissions have changed substantially in the last decade. In this study, we quantify the ARI- and ACI-induced PM2.5 changes for 2013–2021 under different meteorology and emission scenarios using the Weather Research and Forecasting model with Chemistry (WRF-Chem), and we investigate the driving factors behind the changes. Our results show that, in January 2013, when China suffered from the worst PM2.5 pollution, the PM2.5 enhancement induced by ARIs in eastern China (5.59 µg m−3) was larger than that induced by ACIs (3.96 µg m−3). However, the ACI-induced PM2.5 enhancement showed a significantly smaller decrease ratio (51 %) than the ARI-induced enhancement (75 %) for 2013–2021, making ACIs more important for enhancing PM2.5 concentrations in January 2021. Our analyses suggest that the anthropogenic emission reductions played a key role in this shift. Owing to only anthropogenic emission reductions, the ACI-induced PM2.5 enhancement decreased by 43 % in January, which was lower than the decrease ratio of the ARI-induced enhancement (57 %). The relative change in ARI- and ACI-induced PM2.5 enhancement in July was similar to the pattern observed in January, caused by anthropogenic emission reductions. The primary reason for this phenomenon is that the decrease in ambient PM2.5 for 2013–2021 caused a disproportionately small decrease in the liquid water path (LWP) and an increase in the cloud effective radius (Re) under the condition of high PM2.5 concentrations. Therefore, the surface solar radiation attenuation (and, hence, the boundary layer height reduction) caused by ACIs decreased slower than that caused by ARIs. Moreover, the lower decrease ratio of the ACI-induced PM2.5 enhancement was dominated by the lower decrease ratio of ACI-induced secondary PM2.5 component enhancement, which was additionally caused by the smaller decrease ratio of the air temperature reduction and the relative humidity (RH) increase. Our findings indicate that, with the decrease in ambient PM2.5, the ACI-induced PM2.5 enhancement inevitably becomes more important. This needs to be considered in the formulation of control policies to meet the national PM2.5 air quality standard.

Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns

Abstract. A large part of the uncertainty in climate projections comes from uncertain aerosol properties and aerosol–cloud interactions as well as the difficulty in remotely sensing them. The southeastern Atlantic functions as a natural laboratory to study biomass-burning smoke and to constrain this uncertainty. We address these gaps by comparing the Weather Research and Forecasting with Chemistry Community Atmosphere Model (WRF-CAM5) to the multi-campaign observations ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing), and LASIC (Layered Atlantic Smoke Interactions with Clouds) in the southeastern Atlantic in August 2017 to evaluate a large range of the model's aerosol chemical properties, size distributions, processes, and transport, as well as aerosol–cloud interactions. Overall, while WRF-CAM5 is able to represent smoke properties and transport, some key discrepancies highlight the need for further analysis. Observations of smoke composition show an overall decrease in aerosol mean diameter as smoke ages over 4–12 d, while the model lacks this trend. A decrease in the mass ratio of organic aerosol (OA) to black carbon (BC), OA:BC, and the OA mass to carbon monoxide (CO) mixing ratio, OA:CO, suggests that the model is missing processes that selectively remove OA from the particle phase, such as photolysis and heterogeneous aerosol chemistry. A large (factor of ∼2.5) enhancement in sulfate from the free troposphere (FT) to the boundary layer (BL) in observations is not present in the model, pointing to the importance of properly representing secondary sulfate aerosol formation from marine dimethyl sulfide and gaseous SO2 smoke emissions. The model shows a persistent overprediction of aerosols in the marine boundary layer (MBL), especially for clean conditions, which multiple pieces of evidence link to weaker aerosol removal in the modeled MBL than reality. This evidence includes several model features, such as not representing observed shifts towards smaller aerosol diameters, inaccurate concentration ratios of carbon monoxide and black carbon, underprediction of heavy rain events, and little evidence of persistent biases in modeled entrainment. The average below-cloud aerosol activation fraction (NCLD/NAER) remains relatively constant in WRF-CAM5 between field campaigns (∼0.65), while it decreases substantially in observations from ORACLES (∼0.78) to CLARIFY (∼0.5), which could be due to the model misrepresentation of clean aerosol conditions. WRF-CAM5 also overshoots an observed upper limit on liquid cloud droplet concentration around NCLD= 400–500 cm−3 and overpredicts the spread in NCLD. This could be related to the model often drastically overestimating the strength of boundary layer vertical turbulence by up to a factor of 10. We expect these results to motivate similar evaluations of other modeling systems and promote model development to reduce critical uncertainties in climate simulations.

Global Health and Climate Effects of Organic Aerosols from Different Sources.

The impact of aerosols on human health and climate is well-recognized, yet many studies have only focused on total PM2.5 or changes from anthropogenic activities. This study quantifies the health and climate effects of organic aerosols (OA) from anthropogenic, biomass burning, and biogenic sources. Using two atmospheric chemistry models, CAM-chem and GEOS-Chem, our findings reveal that anthropogenic primary OA (POA) has the highest efficiency for health effects but the lowest for direct radiative effects due to spatial and temporal variations associated with population and surface albedo. The treatment of POA as nonvolatile or semivolatile also influences these efficiencies through different chemical processes. Biogenic OA shows moderate efficiency for health effects and the highest for direct radiative effects but has the lowest efficiency for indirect effects due to the reduced high cloud, caused by stabilized temperature profiles from aerosol-radiation interactions in biogenic OA-rich regions. Biomass burning OA is important for cloud radiative effect changes in remote atmospheres due to its ability to be transported further than other OAs. This study highlights the importance of not only OA characteristics such as toxicity and refractive index but also atmospheric processes such as transport and chemistry in determining health and climate impact efficiencies.

A review of recent research progress on the effect of external influences on tropical cyclone intensity change

Over the past four years, significant research has advanced our understanding of how external factors influence tropical cyclone (TC) intensity changes. Research on air-sea interactions shows that increasing the moisture disequilibrium is a very effective way to increase surface heat fluxes and that ocean salinity-stratification plays a non-negligible part in TC intensity change. Vertical wind shear from the environment induces vortex misalignment, which controls the onset of significant TC intensification. Blocking due to upper-level outflow from TCs can reduce the magnitude of vertical wind shear, making for TC intensification. Enhanced TC-trough interactions are vital for rapid intensification in some TC cases because of strengthened warm air advection, but upper-level troughs are found to limit TC intensification in other cases due to dry midlevel air intrusions and increased shear. Aerosol effects on TCs can be divided into direct effects involving aerosol-radiation interactions and indirect effects involving aerosol-cloud interactions. The radiation absorption by the aerosols can change the temperature profile and affect outer rainbands through changes in stability and microphysics. Sea spray and sea salt aerosols are more important in the inner region, where the aerosols increase precipitation and latent heating, promoting more intensification. For landfalling TCs, the intensity decay is initially more sensitive to surface roughness than soil moisture, and the subsequent decay is mainly due to the rapid reduction in surface moisture fluxes. These new insights further sharpen our understanding of the mechanisms by which external factors influence TC intensity changes.

Application of the CHIMERE-WRF Model Complex to Study the Radiative Effects of Siberian Smoke Aerosol in the Eastern Arctic

We describe a computational technology for studying the effects of the aerosol-radiation interaction and calculating regional estimates of the direct (DRE) and semidirect radiative effects (SDRE) of biomass burning (BB) aerosol based on simulations with the CHIMERE chemistry transport model coupled with the WRF meteorological model. The technology was applied to numerical studying the radiative effects of Siberian biomass burning aerosol in the eastern Arctic in the period of July 16–31, 2016. The model simulations show that Siberian smokes, on the whole, had a significant cooling effect on the atmosphere in the eastern Arctic in that period due to the DRE, the value of which at top of the atmosphere was, on average, −6.0 W m−2, being minimal over the snow-ice cover of the ocean (−1.2 W m−2). At the same time, the contribution of the Siberian BB aerosol DRE to the radiative balance of the Arctic atmosphere is found to be offset to a certain extent by the SDRE, which is positive (2.0 W m−2), on average. The SDRE is formed as a result of the multihour aerosol effect on meteorological processes and plays the most important role over the snow-ice Arctic covers, where it exceeds the DRE in absolute value. It has been shown that the SDRE of Siberian BBA in our numerical experiments is mainly due to scattering (rather than absorption) of radiation by aerosol particles.

Superimposed effects of typical local circulations driven by mountainous topography and aerosol–radiation interaction on heavy haze in the Beijing–Tianjin–Hebei central and southern plains in winter

Abstract. Although China's air quality has substantially improved in recent years due to the vigorous emissions reduction, the Beijing–Tianjin–Hebei (BTH) region, especially its central and southern plains at the eastern foot of the Taihang Mountains, has been the most polluted area in China, with persistent and severe haze in winter. Combining meteorology–chemistry coupled model simulations and multiple observations, this study explored the causes of several heavy haze events in this area in January 2017, focusing on local circulations related to mountain terrain. The study results showed that on the weather scale, the configuration of the upper, middle, and lower atmosphere provided favorable weather and water vapor transport conditions for the development of haze pollution. Under the weak weather-scale systems, local circulation played a dominant role in the regional distribution and extreme values of PM2.5. Influenced by the Taihang and Yanshan mountains, vertical circulations and wind convergence zone were formed between the plain and mountain slopes. The vertical distribution of pollutants strongly depended on the intensity and location of the circulation. The circulation with high intensity and low altitude was more unfavorable for the vertical and horizontal diffusion of near-surface pollutants. More importantly, we found that the aerosol–radiation interaction (ARI) significantly amplified the impacts of local vertical circulations on heavy haze by two mechanisms. First, the ARI strengthened the vertical circulations at the lower levels, with the zonal wind speeds increasing by 0.3–0.8 m s−1. Meanwhile, the ARI could cause a substantial downward shift in the vertical circulations (∼ 100 m). Second, the ARI weakened the horizontal diffusion of pollutants by reducing the westerly winds and enhancing wind convergence and southerly winds. Under these two mechanisms, pollutants could only recirculate in a limited space. This superposition of the typical local circulation and the ARI eventually contributed to the accumulation of pollutants and the consequent deterioration of haze pollution in the region.

Combined effect of surface PM2.5 assimilation and aerosol-radiation interaction on winter severe haze prediction in central and eastern China

In this study, the effects of aerosol-radiation interaction (ARI) and data assimilation (DA) during a haze episode in December 2016 are evaluated by four sets of parallel experiments using the atmospheric chemical model GRAPES_Meso5.1/CUACE. The results show that although the BASE experiment without ARI and DA generally captures the variations of particulate matter (PM) and visibility (VIS), it dramatically underestimates the high PM concentrations and overestimates the low VIS on severe haze days. Moreover, the ARI effect is not significant when the aerosol concentration is relatively low (PM2.5 <150 μgm−3). Assimilation of surface PM2.5 corrects the model chemical initial conditions (ICs) and increases the aerosol concentration in severe haze areas. Focusing on the severe pollution periods, the combined effect of ARI and DA significantly improves forecast accuracy and prolongs this improvement, which reduces the average negative biases of PM2.5 and PM10 by 33% and 35%, and increases the average correlation coefficients by 14% and 12%. Moreover, this combined effect also changes the vertical distribution of the atmosphere, especially at a low level, leading to a 2.6 K decrease in potential temperature (PT) and a 7.6% increase in relative humidity (RH) below 300 m. Due to the contributions of PM and RH, the low VIS prediction is significantly improved, with the root mean square error (RMSE) reduced by 30%. The study results show the combined effect of ARI and DA on aerosols and meteorology and suggest the importance of considering ARI and DA simultaneously in the atmospheric chemical model.

African biomass burning affects aerosol cycling over the Amazon

Smoke from vegetation fires affects air quality, atmospheric cycling, and the climate in the Amazon rain forest. A major unknown has remained the quantity of long-range transported smoke from Africa in relation to local and regional fire emissions. Here we quantify the abundance, seasonality, and properties of African smoke in central Amazonia. We show that it accounts for ~ 60% of the black carbon concentrations during the wet season and ~ 30% during the dry season. The African smoke influences aerosol-radiation interactions across the entire Amazon, with the strongest impact on the vulnerable eastern basin, a hot spot of climate and land use change. Our findings further suggest that the direct influence of African smoke has been historically relevant for soil fertilization, the carbon and water cycles, and, thus, the development of the Amazon forest ecosystem, even in the pre-industrial era.

An attribution of the low single-scattering albedo of biomass burning aerosol over the southeastern Atlantic

Abstract. Aerosol over the remote southeastern Atlantic is some of the most sunlight-absorbing aerosol on the planet: the in situ free-tropospheric single-scattering albedo at the 530 nm wavelength (SSA530 nm) ranges from 0.83 to 0.89 within ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) aircraft flights from late August–September. Here we seek to explain the low SSA. The SSA depends strongly on the black carbon (BC) number fraction, which ranges from 0.15 to 0.4. Low organic aerosol (OA)-to-BC mass ratios of 8–14 and modified combustion efficiency values &gt;0.975 point indirectly to the dry, flame-efficient combustion of primarily grass fuels, with back trajectories ending in the miombo woodlands of Angola. The youngest aerosol, aged 4–5 d since emission, occupied the top half of a 5 km thick plume sampled directly west of Angola with a vertically consistent BC:ΔCO (carbon monoxide) ratio, indicating a homogenization of the source emissions. The younger aerosol, transported more quickly off of the continent by stronger winds, overlaid older, slower-moving aerosol with a larger mean particle size and fraction of BC-containing particles. This is consistent with ongoing gas condensation and the coagulation of smaller non-BC particles upon the BC-containing particles. The particle volumes and OA:BC mass ratios of the older aerosol were smaller, attributed primarily to evaporation following fragmentation, instead of dilution or thermodynamics. The CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing: Year 2017) aircraft campaign sampled aerosols that had traveled further to reach the more remote Ascension Island. CLARIFY reported higher BC number fractions, lower OA:BC mass ratios, and lower SSA yet larger mass absorption coefficients compared to this study's. Values from one ORACLES 2017 flight, held midway to Ascension Island, are intermediate, confirming the long-range changes. Overall the data are most consistent with continuing oxidation through fragmentation releasing aerosols that subsequently enter the gas phase, reducing the OA mass, rather than evaporation through dilution or thermodynamics. The data support the following best fit: SSA530nm=0.801+0055⋅(OA:BC) (r=0.84). The fires of southern Africa emit approximately one-third of the world's carbon; the emitted aerosols are distinct from other regional smoke emissions, and their composition needs to be represented appropriately to realistically depict regional aerosol radiative effects.

CALIPSO-observed Southeast Asia biomass-burning influences on aerosol vertical structure in Guangdong-Hong Kong-Macao Greater Bay Area

Southeast Asia (SEA) biomass-burning could exert considerable influences on air quality and stability in the Guangdong-Hong Kong-Macao Great Bay Area (GBA) through long-range transport, while such impacts were typically quantified with numerical modeling which may suffer uncertainties in emissions and model parameterizations. Here we present an observation-based method to quantify such influences of SEA biomass-burning by analyzing 2009–2019 satellite-observed aerosol vertical structure which has enough data records to distinguish the conditions with or without severe biomass-burning impacts based on fire point counts in SEA. Results suggest that the observation-based method successfully captured the SEA biomass-burning days in spring, excluding the irrelevant days as more as possible and avoiding underestimation. Substantial increase of aloft AOD (by 0.21) in GBA is found during the severe SEA biomass-burning days comparing to less severe days, suggesting the enhanced aerosol loading in GBA contributed from the SEA biomass burning. Meanwhile, the near-surface particle size in GBA was increased (CR from 0.606 to 0.673) during severe SEA biomass-burning days, which is opposite to that for the aloft particle size which was decreased (CR from 0.693 to 0.621) driven by the small aerosols originated from biomass-burning SEA. Such phenomenal might be associated with the enhancement of atmospheric static stability in GBA (N2 from 1.34 × 10−4 s−2 to 1.66 × 10−4 s−2) as the abundant aloft aerosols transported from SEA modulates the aerosol vertical structure and associate radiative effects and atmospheric dynamic, results in enhanced aging processes and aerosol particle aggregation under weak ventilation condition. Further, the air pollution in GBA is also aggravated due to the reduced ventilation driven by the enhanced aerosol radiative effects associated with the transported aerosols, as the surface PM2.5 concentrations were increased by 17% (from 29.27 μg /m3 to 34.15 μg /m3) during severe biomass-burning days. Such results demonstrate that our observation-based method with abundant satellites-retrieved aerosol vertical structure information can successfully quantify the influences of SEA biomass-burning on aerosol–radiation interactions and local air pollution over the GBA, which can also be applied in other regions to identify the influences of local sources and regional transport pollution.

The combined effects of heterogeneous chemistry and aerosol-radiation interaction on severe haze simulation by atmospheric chemistry model in Middle-Eastern China

Heterogeneous chemistry and aerosol-radiation interaction (ARI) are considered two of the key mechanisms affecting haze formation and their reasonable parameterizations in atmospherically chemical models play an important role in accurate haze or air quality prediction. However, until the present, their relative contributions to severe haze have rarely been evaluated. Using the double-way atmospherically chemical model GRAPES_Meso5.1/CUACE CW, the relative contributions of heterogeneous chemistry and ARI to PM2.5 are investigated under different pollution levels in Middle-Eastern China (MEC) during December 2016. Study results show that the combined effects of heterogeneous chemistry and ARI generate 29.7% of total PM2.5 mass in MEC of December 2016, of which ARI contributes 19.7%, much higher than heterogeneous chemistry (6.1%). However, heterogeneous chemistry is important for reasonable reproduction of the proportion of secondary inorganic aerosols (SIA) of PM2.5, especially during heavy haze. Both the contributions of heterogeneous chemistry and ARI to PM2.5 increase with the haze pollution aggravation but to different degrees. The contribution of heterogeneous chemistry to modeled PM2.5 concentration rises from 4.0% on clean days to 6.6% under moderate pollution and 7.8% under heavy haze. And that of ARI increases rapidly from 9.1% on clean days to 21.0% under moderate pollution and 29.1% during heavy pollution. It is worth noticing that there is an additional contribution to PM2.5 caused by the combination of heterogeneous chemistry and ARI except for their respective contributions, which reaches up to 7.3% of PM2.5 mass and 18.5% of SIA generation under heavily polluted conditions. This is because ARI further promotes heterogeneous oxidation of SO2 and NOx by increasing the aerosol surface area concentration (SAC), causing additional SIA production via heterogeneous pathways. This work indicates the contribution of ARI to severe haze formation not only by altering meteorological conditions but also by reforming the chemical processes in the model.

Assessing the climate and air quality effects of future aerosol mitigation in India using a global climate model combined with statistical downscaling

Abstract. We studied the potential of using machine learning to downscale global-scale climate model output towards ground station data. The aim was to simultaneously analyze both city-level air quality and regional- and global-scale radiative forcing values for anthropogenic aerosols. As the city-level air pollution values are typically underestimated in global-scale models, we used a machine learning approach to downscale fine particulate (PM2.5) concentrations towards measured values. We first simulated the global climate with the aerosol–climate model ECHAM-HAMMOZ and corrected the PM2.5 values for the Indian megacity New Delhi. The downscaling procedure clearly improved the seasonal variation in the model data. The seasonal trends were much better captured in the corrected PM2.5 than in original ECHAM-HAMMOZ PM2.5 when compared to the reference PM2.5 from the ground stations. However, short-term variations showed less extreme values with the downscaling approach. We applied the downscaling model also to simulations where the aerosol emissions were following two different future scenarios: one following the current legislation and one assuming currently maximum feasible emission reductions. The corrected PM2.5 concentrations for the year 2030 showed that mitigating anthropogenic aerosols improves local air quality in New Delhi, with organic carbon reductions contributing most to these improvements. In addition, aerosol emission mitigation also resulted in negative radiative forcing values over most of India. This was mainly due to reductions in absorbing black carbon emissions. For the two future emission scenarios modeled, the radiative forcing due to aerosol–radiation interactions over India was -0.09±0.26 and -0.53±0.31 W m−2, respectively, while the effective radiative forcing values were -2.1±4.6 and 0.06±3.39 W m−2, respectively. Although accompanied by relatively large uncertainties, the obtained results indicate that aerosol mitigation could bring a double benefit in India: better air quality and decreased warming of the local climate. Our results demonstrate that downscaling and bias correction allow more versatile utilization of global-scale climate models. With the help of downscaling, global climate models can be used in applications where one aims to analyze both global and regional effects of policies related to mitigating anthropogenic emissions.