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Activated cloud droplet fraction versus the below-cloud aerosol hygroscopicity for spring and summer campaigns.
Abstract. A high-resolution soot particle aerosol mass spectrometer (SP-AMS) was used to selectively measure refractory black carbon (rBC) and its associated coating material using both the ensemble size-resolved mass spectral mode and the event trigger single particle (ETSP) mode in Houston, Texas, in summer 2022. This study was conducted as part of the Department of Energy Atmospheric Radiation Measurement (ARM) program's TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign. The study revealed an average (±1σ) rBC concentration of 103 ± 176 ng m−3. Additionally, the coatings on the BC particles were primarily composed of organics (59 %; 219 ± 260 ng m−3) and sulfate (26 %; 94 ± 55 ng m−3). Positive matrix factorization (PMF) analysis of the ensemble mass spectra of BC-containing particles resolved four distinct types of soot aerosol, including an oxidized organic aerosol (OOABC,PMF) factor associated with processed primary organic aerosol, an inorganic sulfate factor (SO4,BC,PMF), an oxidized rBC factor (O-BCPMF), and a mixed mineral dust–biomass burning aerosol factor with significant contribution from potassium (K-BBBC,PMF). Additionally, K-means clustering analysis of the single-particle mass spectra identified eight different clusters, including soot particles enriched in hydrocarbon-like organic aerosol (HOABC,ETSP), sulfate (SO4,BC,ETSP), two types of rBC, OOA (OOABC,ETSP), chloride (ClBC,ETSP), and nitrate (NO3,BC,ETSP). The single-particle measurements demonstrate substantial variation in BC coating thickness with coating-to-rBC mass ratios ranging from 0.1 to 100. The mixing state index (χ), which denotes the degree of homogeneity of the soot aerosol, varied from 4 % to 94 % with a median of 40 %, indicating that the aerosol population lies in between internal and external mixing but has large temporal and source type variability. In addition, a significant fraction of BC-containing particles, a majority enriched with oxidized organics and sulfate, exhibit sufficiently high κ values and diameters conducive to activation as cloud nuclei under atmospherically relevant supersaturation conditions. This finding bears significance in comprehending the aging processes of rBC-containing particles and their activation into cloud droplets. Our analysis highlights the complex nature of soot aerosol and underscores the need to comprehend its variability across different environments for accurate assessment of climate change.
The Arctic is warming at a faster rate than anywhere else on Earth, with rapidly shrinking sea ice extent transforming the region. Depending on chemical and physical properties, atmospheric aerosols directly scatter and/or absorb radiation, serve as cloud droplet and/or ice crystal nuclei, and/or reduce the reflectiveness of the snow surface, thereby altering the atmospheric energy budget. There is a wide spread in the magnitude of simulated arctic aerosol radiative forcing, and significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Increasing local natural and anthropogenic emissions are significant, with uncertain climate impacts due to complex feedbacks. Model evaluations, however, are limited by the dearth of arctic aerosol observations available and an inadequate understanding of arctic aerosol processes. The majority of previous arctic aerosol observations have been made through intensive spring/summer field campaigns, with few intensive measurement studies focused on the fall-winter transition, a period when freeze-up is occurring later and thinning sea ice is resulting in wintertime ice fracturing. Aerosol monitoring at arctic coastal stations has provided knowledge of long-term seasonal trends in aerosol concentrations. The completed ARM field campaign addresses observational and knowledge gaps through detailed aerosol size and chemical composition measurements during the fall-winter transition in the coastal Arctic and through the entire annual cycle in the central Arctic. The observations are improving our understanding of the sources and processes controlling the aerosol population in the rapidly changing Arctic.
Convective clouds play a critical role in the Earth’s climate system. Recent research has shown that a realistic representation of convective processes is critical to constraining climate sensitivity in global climate models. Theoretical and modeling studies showed that aerosols could have strong dynamic feedback to convection in warm and humid environments through enhancing ice-related processes and condensational growth. A few observation-based studies also suggested the influence of aerosols on convective cloud and precipitation properties. However, robust observational quantification of an aerosol effect on convective clouds isolated from other factors remains elusive. Understanding the impact of aerosol on convective clouds requires knowledge of the cloud condensation nuclei (CCN) spectrum, which represents the number of particles that uptake water and form cloud droplets as a function of supersaturation. The water uptake by aerosol is also of critical importance for the direct interaction of aerosol with radiation (i.e., aerosol direct effect) due to light scattering and absorption by aerosol. While both droplet activation under supersaturated conditions (i.e., relative humidity RH > 100%) and the hygroscopic growth under sub-saturated conditions (i.e., RH < 100%) are strongly influenced by particle hygroscopicity, the thermodynamic regimes and measurement methods are quite different. Aerosol particles, especially organic particles, can exhibit higher hygroscopicity for droplet activation than that for hygroscopic growth. In the subsaturated regime, the hygroscopicity of organic particles can also vary strongly with RH. However, global climate models usually treat organic species in aerosols with a constant hygroscopicity, potentially introducing substantial uncertainties in the quantification of aerosol radiative effects.
The Amazon basin is important for understanding the global climate because of its carbon cycle and as a laboratory for obtaining basic knowledge of the continental background atmosphere. Aerosol particles play an important role in the climate and weather, and knowledge of their compositions and mixing states is necessary to understand their influence on the climate. For this study, we collected aerosol particles from the Amazon basin during the Green Ocean Amazon (GoAmazon2014/5) campaign (February to March 2014) at the T3 site, which is located about 70 km from Manaus, and analyzed them using transmission electron microscopy (TEM). TEM has better spatial resolution than other instruments, which enables us to analyze the occurrences of components that attach to or are embedded within other particles. Based on the TEM results of more than 10 000 particles from several transport events, this study shows the occurrences of individual particles including compositions, size distributions, number fractions, and possible sources of materials that mix with other particles. Aerosol particles during the wet season were from both natural sources such as the Amazon forest, Saharan desert, Atlantic Ocean, and African biomass burning and anthropogenic sources such as Manaus and local emissions. These particles mix together at an individual particle scale. The number fractions of mineral dust and sea-salt particles increased almost 3-fold when long-range transport (LRT) from the African continent occurred. Nearly 20 % of mineral dust and primary biological aerosol particles had attached sea salts on their surfaces. Sulfates were also internally mixed with sea-salt and mineral dust particles. The TEM element mapping images showed that several components with sizes of hundreds of nanometers from different sources commonly occur within individual LRT aerosol particles. We conclude that many aerosol particles from natural sources change their compositions by mixing during transport. The compositions and mixing states of these particles after emission result in changes in their hygroscopic and optical properties and should be considered when assessing their effects on climate.
Beijing has been suffering from frequent severe air pollution events, with concentrations affected significantly by the mixed-layer height. Major efforts have been made to study the physico-chemical properties, compositions, and sources of aerosol particles at ground level. However, little is known about the morphology, elemental composition, and mixing state of aerosol particles above the mixed layer. In this work, we collected individual aerosol particles simultaneously at ground level (2 m above ground) and above the mixed layer in urban Beijing (within the Atmospheric Pollution and Human Health in a Chinese Megacity, APHH-Beijing, 2016 winter campaign). The particles were analyzed offline by transmission electron microscopy coupled with energy dispersive X-ray spectroscopy. Our results showed that the relative number contribution of mineral particles to all measured particles was much higher during non-haze periods (42.5 %) than haze periods (18.1 %); in contrast, internally mixed particles contributed more during haze periods (21.9 %) than non-haze periods (7.2 %) at ground level. In addition, more mineral particles were found at ground level than above the mixed-layer height. Around 20 % of individual particles showed core–shell structures during haze periods, whereas only a few core–shell particles were observed during non-haze periods (2 %). The results showed that the particles above the mixed layer were more aged, with a larger proportion of organic particles originating from coal combustion. Our results indicate that a large fraction of the airborne particles above the mixed layer come from surrounding areas influenced by coal combustion activities. This source contributes to the surface particle concentrations in Beijing when polluted air is mixed down to the ground level.
Abstract. Black carbon (BC) exerts a notable warming effect due to its strong light absorption, largely influenced by its “mixing state”. However, due to computational constraints, the mixing state is challenging to accurately represent in large-scale models. In this study, we employ a particle-resolved model to simulate the evolution of BC mixing state based on field observation. Our result shows that aerosol compositions, coating thickness (CT) distribution, and optical properties of BC aerosols all exhibit a tendency toward a steady state with a characteristic timescale of less than 1 d, considerably shorter than the BC atmospheric lifetime. The rapid attainment of a steady state suggests that it is reasonable to disregard this pre-steady-state period and instead concentrate on the average properties of BC across extensive spatial and temporal scales. The distribution of CT follows an exponential linear distribution and can be characterized by a single slope parameter k. This distribution is independent of the BC core's distribution. In the model simulation, the mean CT, equivalent to the 1/k, is 62 nm, which is consistent with the statistical results indicating a mean CT of 63 nm. Utilizing the slope parameter k, which effectively characterizes the CT distribution under the steady-state simplifying assumption, the BC absorption enhancement closely corresponds to the results obtained via the particle-resolved method. This study simplifies the BC mixing state description and yields a precise evaluation of the BC optical properties, which has the potential utility for modeling efforts in the refinement of the assessment of BC's radiative effects.
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Black carbon (BC) plays an important role in the climate system because of its strong warming effect, yet the magnitude of this effect is highly uncertain owing to the complex mixing state of aerosols. Here we build a unified theoretical framework to describe BC’s mixing states, linking dynamic processes to BC coating thickness distribution, and show its self-similarity for sites in diverse environments. The size distribution of BC-containing particles is found to follow a universal law and is independent of BC core size. A new mixing state module is established based on this finding and successfully applied in global and regional models, which increases the accuracy of aerosol climate effect estimations. Our theoretical framework links observations with model simulations in both mixing state description and light absorption quantification.
The Amazon basin is important for understanding the global climate both because of its carbon cycle and as a laboratory for obtaining basic knowledge of the continental background atmosphere. Aerosol particles play an important role in the climate and weather, and knowledge of their compositions and mixing states is necessary to understand their influence on the climate. For this study, we collected aerosol particles from the Amazon basin during the Green Ocean Amazon (GoAmazon2014/5) campaign (February to March 2014) at the T3 site, which locates about 70 km from Manaus, and analyzed using transmission electron microscopy (TEM). TEM has better spatial resolution than other instruments, which enables us to analyse the occurrences of components that attach to or are embedded within other particles. Based on the TEM results of more than 10,000 particles from several transport events, this study shows the occurrences of individual particles including compositions, size distributions, number fractions, and possible sources of materials that mix with other particles. Aerosol particles during the wet season were from both natural sources such as the Amazon forest, Saharan desert, Atlantic Ocean, and African biomass burning and anthropogenic sources such as Manaus and local emissions. These particles mix together at an individual particle scale. The number fractions of mineral dust and sea-salt particles increased almost three-fold when long-range transport (LRT) from the African continent occurred. Nearly 20 % of mineral dust and primary biological aerosol particles attached sea salts on their surfaces. Sulfates were also internally mixed with sea-salt and mineral dust particles. The TEM element mapping images showed that several components with sizes of hundreds of nanometres from different sources commonly occur within individual LRT aerosol particles. We conclude that many aerosol particles from natural sources change their compositions by mixing during transport. The compositions and mixing states of these particles after emission result in changes in their hygroscopic and optical properties and should be considered when assessing their effects on climate.
As the Arctic rapidly warms, sea ice extent is decreasing and oil and gas extraction activities are expanding. Local combustion emissions affect the Arctic atmospheric aerosol chemical mixing state (the distribution of chemical species across the aerosol population), which impacts climate-relevant properties. Bulk and single-particle measurements of submicron aerosols were conducted at Oliktok Point, Alaska within the North Slope of Alaska oil fields. In this work, we quantify aerosol diversity using online single-particle mass spectrometry data (32,880 individual particles), offline single-particle microscopy data (20,912 individual particles), and online bulk aerosol mass spectrometry and aethalometer data. This method was used to derive individual particle mass fractions for both refractory and non-refractory material within distinct particle types. Single-particle, average single-particle, and bulk population diversities (D i , D α , D γ , respectively) and mixing state indices (χ) were calculated for the data set. Calculated D i values were generally low (2.2 ± 0.6), as individual particle masses were dominated by a few chemical species of interest. Aged aerosol particles (those internally mixed with nitrate and/or sulfate) exhibited higher D i values (>3) compared to recently emitted (fresh) aerosol particles. During oil field plume periods, D α values approached three due to the abundance of diesel combustion particles, which were rich in sulfate, black carbon, and organic aerosol. Overall, the submicron aerosol population within the Arctic oil fields was found to be relatively externally mixed (χ < 50%), due to the constant local emissions within oil fields combining with background aerosol and locally emitted sea spray aerosol at the coastal site.
Mixing states of aerosol particles are crucial for understanding the role of aerosols in influencing air quality and climate. However, a fundamental understanding of the complex mixing states is still lacking because most traditional analysis techniques only reveal bulk chemical and physical properties with limited surface and 3-D information. In this research, 3-D molecular imaging enabled by ToF-SIMS was used to elucidate the mixing states of PM 2.5 samples obtained from a typical Beijing winter haze event. In light pollution cases, a thin organic layer covers separated inorganic particles, while in serious pollution cases, ion exchange and an organic-inorganic mixing surface on large-area particles were observed. Finally, the new results provide key 3-D molecular information of mixing states, which is highly desirable for reducing uncertainty and bias in representing aerosol-cloud interactions in current Earth System Models, and improving the understanding of aerosols on air quality and human health.
Accurate modeling of the scattering and absorption of ultraviolet and visible radiation by aerosols is essential for accurate simulations of atmospheric chemistry and climate. Closure studies using in situ measurements of aerosol scattering and absorption can be used to evaluate and improve models of aerosol optical properties without interference from model errors in aerosol emissions, transport, chemistry, or deposition rates. Here we evaluate the ability of four externally mixed, fixed size distribution parameterizations used in global models to simulate submicron aerosol scattering and absorption at three wavelengths using in situ data gathered during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. The four models are the NASA Global Modeling Initiative (GMI) Combo model, GEOS-Chem v9- 02, the baseline configuration of a version of GEOS-Chem with online radiative transfer calculations (called GC-RT), and the Optical Properties of Aerosol and Clouds (OPAC v3.1) package. We also use the ARCTAS data to perform the first evaluation of the ability of the Aerosol Simulation Program (ASP v2.1) to simulate submicron aerosol scattering and absorption when in situ data on the aerosol size distribution are used, and examine the impact of different mixing rules for black carbon (BC) on the results. We find that the GMI model tends to overestimate submicron scattering and absorption at shorter wavelengths by 10-23 percent, and that GMI has smaller absolute mean biases for submicron absorption than OPAC v3.1, GEOS-Chem v9-02, or GC-RT. However, the changes to the density and refractive index of BC in GCRT improve the simulation of submicron aerosol absorption at all wavelengths relative to GEOS-Chem v9-02. Adding a variable size distribution, as in ASP v2.1, improves model performance for scattering but not for absorption, likely due to the assumption in ASP v2.1 that BC is present at a constant mass fraction throughout the aerosol size distribution. Using a core-shell mixing rule in ASP overestimates aerosol absorption, especially for the fresh biomass burning aerosol measured in ARCTAS-B, suggesting the need for modeling the time-varying mixing states of aerosols in future versions of ASP.
Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.
Uncertainty in the representation of biomass burning (BB) aerosol composition and optical properties in climate models contributes to a range in modeled aerosol effects on incoming solar radiation. Depending on the model, the top-of-the-atmosphere BB aerosol effect can range from cooling to warming. By relating aerosol absorption relative to extinction and carbonaceous aerosol composition from 12 observational datasets to nine state-of-the-art Earth system models/chemical transport models, we identify varying degrees of overestimation in BB aerosol absorptivity by these models. Modifications to BB aerosol refractive index, size, and mixing state improve the Community Atmosphere Model version 5 (CAM5) agreement with observations, leading to a global change in BB direct radiative effect of -0.07 W m -2 , and regional changes of -2 W m -2 (Africa) and -0.5 W m -2 (South America/Temperate). Our findings suggest that current modeled BB contributes less to warming than previously thought, largely due to treatments of aerosol mixing state.
Abstract. Long-range transport of continental emissions has a far-reaching influence over remote regions, resulting in substantial change in the size, morphology, and composition of the local aerosol population and cloud condensation nuclei (CCN) budget. Here, we investigate the physicochemical properties of atmospheric particles collected on board a research aircraft flown over the Azores during the winter 2018 Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) campaign. Particles were collected within the marine boundary layer (MBL) and free troposphere (FT) after long-range atmospheric transport episodes facilitated by dry intrusion (DI) events. Chemical and physical properties of individual particles were investigated using complementary capabilities of computer-controlled scanning electron microscopy and X-ray spectromicroscopy to probe particle external and internal mixing state characteristics. Furthermore, real-time measurements of aerosol size distribution, cloud condensation nuclei (CCN) concentration, and back-trajectory calculations were utilized to help bring into context the findings from offline spectromicroscopy analysis. While carbonaceous particles were found to be the dominant particle type in the region, changes in the percent contribution of organics across the particle population (i.e., external mixing) shifted from 68 % to 43 % in the MBL and from 92 % to 46 % in FT samples during DI events. This change in carbonaceous contribution is counterbalanced by the increase in inorganics from 32 % to 57 % in the MBL and 8 % to 55 % in FT. The quantification of the organic volume fraction (OVF) of individual particles derived from X-ray spectromicroscopy, which relates to the multi-component internal composition of individual particles, showed a factor of 2.06 ± 0.16 and 1.11 ± 0.04 increase in the MBL and FT, respectively, among DI samples. We show that supplying particle OVF into the κ-Köhler equation can be used as a good approximation of field-measured in situ CCN concentrations. We also report changes in the κ values in the MBL from κMBL, non-DI=0.48 to κMBL, DI=0.41, while changes in the FT result in κFT, non-DI=0.36 to κFT, DI=0.33, which is consistent with enhancements in OVF followed by the DI episodes. Our observations suggest that entrainment of particles from long-range continental sources alters the mixing state population and CCN properties of aerosol in the region. The work presented here provides field observation data that can inform atmospheric models that simulate sources and particle composition in the eastern North Atlantic.
Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (d va ) within typical instrumental ranges from ~100–200 nm (lower limit) to ~2–3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to ~10 3 ) and high signal-to-noise ratio (up to ~10 4 ) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra r avg-pos =0.74 ± 0.12 and average negative spectra r avg-neg =0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from “blind experiments” showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles.
Black carbon (BC) absorbs solar radiation, leading to a strong but uncertain warming effect on climate. A key challenge in modeling and quantifying BC’s radiative effect on climate is predicting enhancements in light absorption that result from internal mixing between BC and other aerosol components. Modeling and laboratory studies show that BC, when mixed with other aerosol components, absorbs more strongly than pure, uncoated BC; however, some ambient observations suggest more variable and weaker absorption enhancement. We show that the lower-than-expected enhancements in ambient measurements result from a combination of two factors. First, the often used spherical, concentric core-shell approximation generally overestimates the absorption by BC. Second, and more importantly, inadequate consideration of heterogeneity in particle-to-particle composition engenders substantial overestimation in absorption by the total particle population, with greater heterogeneity associated with larger model–measurement differences. We show that accounting for these two effects—variability in per-particle composition and deviations from the core-shell approximation—reconciles absorption enhancement predictions with laboratory and field observations and resolves the apparent discrepancy. Furthermore, our consistent model framework provides a path forward for improving predictions of BC’s radiative effect on climate.