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At least 19 records

Steady-state mixing state of black carbon aerosols from a particle-resolved model

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.

Zhang, Zhouyang↗

Instability of steady-state mixed-state symmetry-protected topological order to strong-to-weak spontaneous symmetry breaking

Recent experimental progress in controlling open quantum systems enables the pursuit of mixed-state nonequilibrium quantum phases. We investigate whether open quantum systems hosting mixed-state symmetry-protected topological states as steady states retain this property under symmetric perturbations. Focusing on the decohered cluster state – a mixed-state symmetry-protected topological state protected by a combined strong and weak symmetry – we construct a parent Lindbladian that hosts it as a steady state. This Lindbladian can be mapped onto exactly solvable reaction-diffusion dynamics, even in the presence of certain perturbations, allowing us to solve the parent Lindbladian in detail and reveal previously-unknown steady states. Using both analytical and numerical methods, we find that typical symmetric perturbations cause strong-to-weak spontaneous symmetry breaking at arbitrarily small perturbations, destabilize the steady-state mixed-state symmetry-protected topological order. However, when perturbations introduce only weak symmetry defects, the steady-state mixed-state symmetry-protected topological order remains stable. Additionally, we construct a quantum channel which replicates the essential physics of the Lindbladian and can be efficiently simulated using only Clifford gates, Pauli measurements, and feedback.

Shah, Jeet [University of Maryland, College Park, ↗

Mixed-state geometric phases of coherent and squeezed spin states

Two mixed-state geometric phases, known as the Uhlmann phase and interferometric geometric phase (IGP), of spin coherent states (CSSs) and spin squeezed states (SSSs) are analyzed. Exact solutions and numerical results of selected examples are presented. For the 𝑗=3/2 CSS, the Uhlmann phase exhibits finite-temperature topological phase transitions characterized by abrupt jumps. The IGP for the same state similarly shows discontinuous jumps as the temperature varies. In the case of the 𝑗=1 one-axis SSS, both the Uhlmann phase and IGP display discrete finite-temperature jumps. By contrast, the 𝑗=1 two-axis SSS shows no such transitions because the Uhlmann phase and IGP both vary smoothly with temperature. Here, we also briefly discuss potential realizations and simulations related to these phenomena in spin systems.

Geometric & topological phases↗

Improving BC Mixing State and CCN Activity Representation With Machine Learning in the Community Atmosphere Model Version 6 (CAM6)

Abstract Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non‐BC species and large mass ratio of coating to BC ( R BC , the mass ratio of non‐BC species to BC in BC‐containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle‐resolved simulations to the CAM6 with MAM4 (MAM4‐ML). In MAM4‐ML, we use R BC to partition accumulation mode particles into two new modes, BC‐free particles and BC‐containing particles. We adjust R BC to make the modeled BC mixing state index ( χ mode ) match the one predicted by the ML model ( χ ML ). On a global average, the mass fraction of BC‐containing particles in accumulation mode decreases from 100% (MAM4‐default) to 48% (MAM4‐ML). The globally averaged χ mode decreases from 78% (MAM4‐default) to 63% (MAM4‐ML, 19% reduction) and agrees well with χ ML (66%). The R BC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC‐containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs.

Meteorology & Atmospheric Sciences↗

Aerosol Particle Mixing State and Composition at AMF3 (Interim Field Campaign Report)

The campaign is designed to support deployment of aerosol sampling equipment at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s third ARM Mobile Facility (AMF3) to enable both singe-particle and bulk characterization of the aerosol particles at the field site in Bankhead National Forest, northern Alabama. We are proposing to do this work as part of our proposal “Generalizing aerosol mixing state: synthesis from observations and connection to models,” which has the pre-proposal tracking number PRE-0000035878. The full proposal has Dr. Rachel O’Brien as the Principal Investigator (PI) and Dr. Andy Ault and Dr. Nicole Riemer as Co-PIs. We sought to deploy instruments in winter 2025 and summer 2025 to obtain samples in different seasons, but were delayed by AMF3 set-up and availability of students and PIs. We just completed our first deployment this summer (2025) and we are interested in obtaining samples during this upcoming fall and winter to see the seasonal trends in aerosol mixing state at the site. This will provide a comparison of the impact of biogenic emissions on the mixing state and the chemical composition of the aerosol particles. Overall, the proposed study will provide key information regarding the mixing state of aerosol particles at AMF3 with direct ties to impacts of the particles on cloud formation and light scattering/absorption. From our deployment that ended las week we have some visible observations from our samples. We are observing a regular amount of black carbon on stage 6 of our Micro-Orifice Uniform Deposit Impactor (MOUDI) and we have also observed some short, large increases in aerosol loading. We hope to continue observations of these two features to determine the sources/aging for the black carbon and the physical mixing state as well as the sources for the short (a few minutes) increases in the aerosol loading and determine if the source for these is dust or sea salt or another source. We are also interested in comparing the black carbon we see here to samples collected during the agriculture burns in January/February and in comparing the larger particles to bioaerosols in the spring. To obtain these comparisons, we will need to collect more samples in the other seasons. Finally, we have some size-resolved particle collectors that can be deployed at the same time as the tethered balloon launches. We have discussed with Swarup China about trying to get the timing to work in August and we are interested in coordinating again later, if possible. This will give us ground-level and vertical aerosol mixing state sample sets that will be very exciting to analyze.

54 ENVIRONMENTAL SCIENCES↗

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗

Effective rationality for local unitary invariants of mixed states of two qubits

Abstract We calculate the field of rational local unitary invariants for mixed states of two qubits, by employing methods from algebraic geometry. We prove that this field is rational (i.e. purely transcendental), and that it is generated by nine algebraically independent polynomial invariants. We do so by constructing a relative section, in the sense of invariant theory, whose Weyl group is a finite abelian group. From this construction, we are able to give explicit expressions for the generating invariants in terms of the Bloch matrix representation of mixed states of two qubits. We also prove similar rationality results for the local unitary invariants of symmetrically mixed states of two qubits. We also provide a sketch of how to generalize our results to the case of an arbitrary number of qubits. Our results apply to both complex-valued and real-valued invariants.

Physics↗

Assessing the link between aerosol mixing state, structure and composition and their optical properties: Ascension Island as a testbed for the South‐East Atlantic aerosol regimes

Forest and savanna fires are a major source of pollution over the globe. Such fire events emit to the atmosphere a considerable amount of “fluffy” fractal black looking particles that are often referred to as black carbon (BC) or soot aerosols. In fact, BC particles (aerosols) emitted from savanna and agricultural fires over the African continent play an important role in the region’s and the global climate. These fires occur each year between July and October, which is referred to as the biomass burning (BB) season and are considered among the globe's largest man-made emission sources of BC particles. However, during these fire events, not only BC particles are emitted, but also other types of particles and gases that can interact with each other to create new particles, generating a slew of particles often generally referred to as BB aerosols. Although the majority of the fire emissions occur inland in the sub-Saharan part of Africa, their effect reaches far beyond the continent due to the prevailing easterly winds, which transport those aerosols over the South-East Atlantic (SEA) ocean, off the west-coast of Africa. The reason why these particles are so important to the regional and global climate is that they absorb sunlight radiation, which overall warms the climate. However, the magnitude of this warming effect is highly uncertain and depends upon a multitude of aspects. Our overarching goal for this project was to better understand the changes in the aerosol properties as they transport from fire sources downstream toward the ocean and how this can eventually affect the earth's radiative budget in terms of warming or cooling. Following the above, our work here was focused on the investigation of the African BB aerosol plumes mixing state (mixing of BB aerosols and other aerosol types), composition and size distribution as they transport from the African continent towards the SEA ocean, and their link with some of the commonly measurable bulk optical properties such as mass absorption coefficient (MAC) and single scattering albedo (SSA). We utilized three field missions that were conducted over the SEA ocean between 2016 and 2018. Specifically, we used (1) ground-based measurements from the DOE ARM Mobile Facility (AMF1), which was deployed at Ascension Island (ASI) for the LASIC (Layered Atlantic Smoke Interactions with Clouds) campaign between June 2016 and October 2017, (2) airborne measurements from the UK CLARIFY (Clouds and Aerosol Radiative impacts and Forcing) campaign during Aug-Sep-2017, and (3) airborne measurements from the ORACLES (Observations of Aerosols above Clouds and their interactions) campaign during Aug-2017, and Sep-Oct-2018. The three campaigns cover a relatively large region, from the western African coast on the east towards Ascension Island in the middle of the SEA to the west. We used the data gathered by these campaigns to find how BB properties and composition change from near emission sources (the ORACLES campaign flights) downstream (the CLARIFY flights and the ground based LASIC measurements). We used particle trajectory following methodologies to connect the measurements from the different campaigns, which allowed us to follow a certain aerosol plume (airmass) from near-source towards Ascension Island. We found out that atmospheric aging processes governed by the UV light from the sun (photochemistry) and cloud processes (aqueous chemistry) govern the changes seen in the particle composition during the transport were more dominant in dictating aerosol composition than specific emission composition or source types. We assessed how aerosol optical properties change during the BB season and what are the main drivers of this change. We found that the enhanced ratio of BC to CO is well correlated with single scattering albedo (SSA) and mass absorption coefficient (MACBC), providing a simple way to estimate the aerosol optical characteristics in the south-eastern Atlantic Ocean. From the analysis of the location of BB, the primary source fuel, the water content in the fuel, combined with the mean cloud cover and precipitation in the transport areas of the BB plume, we conclude that the increase in BC/CO from June to August is likely to be caused by burning becoming more flaming (hot fires), and the decrease in BC/CO in September and October may be caused by smoldering (colder) fires. We found that aerosol hygroscopicity increases with decreasing altitude below 2km, and that enhanced BB hygroscopicity at lower altitudes is mainly due to a lower organic aerosol (OA) fraction, increased sulfate fraction, and greater hygroscopicity parameter of OA at lower altitudes.

54 ENVIRONMENTAL SCIENCES↗

Diagnostics of Mixed-State Topological Order and Breakdown of Quantum Memory

Topological quantum memory can protect information against local errors up to finite error thresholds. Such thresholds are usually determined based on the success of decoding algorithms rather than the intrinsic properties of the mixed states describing corrupted memories. Here we provide an intrinsic characterization of the breakdown of topological quantum memory, which both gives a bound on the performance of decoding algorithms and provides examples of topologically distinct mixed states. We employ three information-theoretical quantities that can be regarded as generalizations of the diagnostics of ground-state topological order, and serve as a definition for topological order in error-corrupted mixed states. We consider the topological contribution to entanglement negativity and two other metrics based on quantum relative entropy and coherent information. In the concrete example of the two-dimensional (2D) Toric code with local bit-flip and phase errors, we map three quantities to observables in 2D classical spin models and analytically show they all undergo a transition at the same error threshold. This threshold is an upper bound on that achieved in any decoding algorithm and is indeed saturated by that in the optimal decoding algorithm for the Toric code. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Noisy Approach to Intrinsically Mixed-State Topological Order

We propose a general framework for studying two-dimensional (2D) topologically ordered states subject to local correlated errors and show that the resulting mixed state can display (imTO)—topological order that is not expected to occur in the ground state of 2D local gapped Hamiltonians. Specifically, we show that decoherence, previously interpreted as anyon condensation in a doubled Hilbert space, is more naturally phrased as, and provides a physical mechanism for, “gauging out” anyons in the original Hilbert space. We find that gauging out anyons generically results in imTO, with the decohered mixed state strongly symmetric under certain anomalous 1-form symmetries. This framework lays bare a striking connection between the decohered density matrix and , which can appear as anomalous surface states of three-dimensional topological orders. Through a series of examples, we show that the decohered state can display a classical memory, encode logical qubits (i.e., exhibit a quantum memory), and even host chiral or nonmodular topological order. We argue that a partial classification of imTO is given in terms of nonmodular braided-fusion categories. Published by the American Physical Society 2025

Sohal, Ramanjit (ORCID:0000000292975715)↗

Semi‐Volatile Organic Partitioning Improves Simulation of Biomass Burning Aerosol Mixing State Evolution

Biomass burning aerosols significantly contribute to atmospheric composition and radiative forcing, with black carbon (BC) mixing states critically influencing optical properties and climate impacts. Recent field observations reveal a systematic three‐phase evolution in BC coating thickness during plume aging: rapid initial growth, quasi‐equilibrium, and gradual coating loss. Current models misrepresent this evolution due to oversimplified treatment of organic aerosol volatility. Here we demonstrate that incorporating semi‐volatile organic partitioning through the MATRIX‐VBS model fundamentally improves simulation accuracy compared to traditional non‐volatile approaches. Evaluation against four field campaigns spanning fresh to aged plumes shows MATRIX‐VBS successfully captures the observed three‐phase pattern, and global application reveals universal three‐phase evolution with substantial regional variations. These advances address critical gaps in aerosol mixing state representation and provide essential improvements for climate model predictions in wildfire‐affected regions.

Gao, Chloe Yuchao [Fudan Univ., Shanghai (China); ↗

Holographic View of Mixed-State Symmetry-Protected Topological Phases in Open Quantum Systems

We establish a holographic duality between d -dimensional mixed-state symmetry-protected topological (mSPT) phases and ( d + 1 ) -dimensional subsystem symmetry-protected topological (SSPT) states. Specifically, we show that the reduced density matrix of the boundary layer of a ( d + 1 ) -dimensional SSPT state with subsystem symmetry S and global symmetry G corresponds to a d -dimensional mSPT phase with strong S and weak G symmetries. Conversely, we demonstrate that the wave function of an SSPT state can be constructed by replicating the density matrix of the corresponding lower-dimensional mSPT phase. This mapping links the density matrix in lower dimensions to the entanglement properties of higher-dimensional wave functions, providing an approach for analyzing nonlinear quantities and quantum information metrics in mixed-state systems. Our duality offers a new perspective for studying intrinsic mSPT phases that are unique to open quantum systems, without pure-state analogues. We show that strange correlators and twisted Rényi- N correlators can diagnose these nontrivial phases and we explore their connection to strange correlators in pure-state SSPT phases. Furthermore, we discuss several implications of this holographic duality, including a method for preparing intrinsic mSPT phases through the duality. Published by the American Physical Society 2025

Sun, Shijun (ORCID:0000000168880030)↗

Chemical Composition and Mixing State of Wintertime Aerosol from the European Arctic Site of Ny-Ålesund, Svalbard

The Arctic is rapidly warming, and aerosols play an increasingly important role by scattering and absorbing sunlight and by participating in cloud formation. Their optical and cloud-forming properties depend on the mixing state and chemical composition, but observations of these features remain limited. This study comprehensively characterizes 25,254 individual particles collected at Ny-Ålesund, Svalbard (November −December 2020), using microspectroscopy techniques to investigate their size, morphology, mixing state, and chemical composition. Fresh sea salt aerosols (SSA) were identified as the most abundant (∼85%), of the total observed aerosol population, with potential sources from sea spray and blowing snow. Air masses originating from the Arctic Ocean surrounding Svalbard likely contribute to increased concentrations of sub-micrometer “Fresh SSA” particles. “Aged SSA” particles (7.4%) are enriched in sulfur and nitrogen, compared to “Fresh SSA”. These elevated ratios may result from various atmospheric aging processes including the uptake of sulfuric and nitric acids. Here, our results suggest that aged SSA, with sizes larger than 300 nm, likely underwent chlorine depletion by sulfuric and nitric acids during transport. Additionally, elemental analysis reveals that both fresh and aged SSA can mix with dust particles, regardless of the SSA size (49.9% in sub-micrometer size and 50.1% in super-micrometer size, respectively). Dust particles are efficient ice-nucleating particles (INPs), and SSA is known to act as cloud condensation nuclei (CCN), and therefore, their mixtures may inherit both properties. The non-negligible number (4.4%) of SSA-dust mixtures underscores the importance of these particles as potential sources of CCN and INP in the Arctic atmosphere.

Arctic↗

Locally purified maximally mixed states at scale: Entanglement pruning and symmetries

Locally Purified Density Operators (LPDOs) are state-of-the-art tensor network ansatze candidates that efficiently represent mixed quantum states at scale. However, given their non-uniqueness, their representational complexity is generally sub-optimal in practical computations. Here, in this work we perform a comprehensive numerical and analytical analysis and resolve this issue in the experimentally relevant limit where noise depolarizes the density operator into a maximally mixed state. To resolve the sub-optimality issue, we analyze two numerical tools, one analytic method, and detail the relations between them. The numerical tools used are fidelity-preserving truncations and isometric gauge transformations leveraging Riemannian optimizations over entropic objective functions. In addition, by invoking the injectivity and symmetry constraints of the maximally mixed LPDO, we also present analytical closed-form expressions for the disentangler and discuss their relation to numerical optimizers. Further, away from the maximally mixed state, our simulations highlight how the truncation threshold smoothly interpolate, as a function of depolarization, between established matrix product results and our new results. Our work shows how, by minimizing the resources required to represent key states of practical interest in experiment, the efficiency of tensor network algorithms can be substantially increased. This paves the path for uncovering tensor network’s fundamental scalability limits and latent potential in representing the wide locus of mixed quantum states that are accessible on near-term quantum devices.

Gangapuram, Amit Jamadagni [Oak Ridge National Lab↗

Probing scrambling and operator size distributions using random mixed states and local measurements

The dynamical spreading of quantum information through a many-body system, typically called scrambling, is a complex process that has proven to be essential to describe many properties of out-of-equilibrium quantum systems. Scrambling can, in principle, be fully characterized via the use of out-of-time-ordered correlation functions, which are notoriously hard to access experimentally. In this work, we put forward an alternative toolbox of measurement protocols to experimentally probe scrambling by accessing properties of the operator size probability distribution, which tracks the size of the support of observables in a many-body system over time. Our measurement protocols require the preparation of separable mixed states together with local operations and measurements, and combine the tools of randomized operations, a modern development of near-term quantum algorithms, with the use of mixed states, a standard tool in NMR experiments. We demonstrate how to efficiently probe the probability-generating function of the operator distribution and discuss the challenges associated with obtaining the moments of the operator distribution. We further show that manipulating the initial state of the protocol allows us to directly obtain the individual elements of the distribution for small system sizes. Published by the American Physical Society 2024

Blocher, Philip Daniel (ORCID:0000000163027567)↗

Data for The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations

This dataset contains the values directly shown in the figures of the article "The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations". This article is in preparation for submission to the journal Atmospheric Chemistry and Physics. The dataset consists of 12 NetCDF files processed from the raw output of the PartMC model. It does not include the theoretical values of frozen fraction, which can be computed using the equations provided in the paper. *New in V2: adding data for a newly included figure (INP_spectrum.nc), removing files that are no longer used in the revised manuscript figures (e.g., UNC_A_ratio=0.9_Dp=0.1.nc, UNC_A_ratio=0.9_Dp=10.0.nc, UNC_A_ratio=0.1_Dp=0.1.nc, and UNC_A_ratio=0.1_Dp=10.0.nc), and updating README.pdf accordingly.

Aerosol mixing state↗

Chemical properties and single-particle mixing state of soot aerosol in Houston during the TRACER campaign

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.

54 ENVIRONMENTAL SCIENCES↗