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At least 109 records · Page 6

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

The objective of the cyclotron radiation emission spectroscopy (CRES) technology is to build precise particle energy spectra. This is achieved by identifying the start frequencies of charged particle trajectories which, when exposed to an external magnetic field, leave semi-linear profiles (called tracks) in the time–frequency plane. Due to the need for excellent instrumental energy resolution in application, highly efficient and accurate track reconstruction methods are desired. Deep learning convolutional neural networks (CNNs) - particularly suited to deal with information-sparse data and which offer precise foreground localization—may be utilized to extract track properties from measured CRES signals (called events) with relative computational ease. In this work, we develop a novel machine learning based model which operates a CNN and a support vector machine in tandem to perform this reconstruction. A primary application of our method is shown on simulated CRES signals which mimic those of the Project 8 experiment—a novel effort to extract the unknown absolute neutrino mass value from a precise measurement of tritium β - -decay energy spectrum. When compared to a point-clustering based technique used as a baseline, we show a relative gain of 24.1% in event reconstruction efficiency and comparable performance in accuracy of track parameter reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Microscopic theory of onset of decaging and bond-breaking activated dynamics in ultradense fluids with strong short-range attractions

We theoretically study thermally activated “in cage” elementary dynamical processes that precede full structural relaxation in ultra-dense particle liquids interacting via strong short range attractive forces. The analysis is based on a microscopic theory formulated at the particle trajectory level built on the dynamic free energy concept and an explicit treatment of how attractive forces control the formation and lifetime of physical bonds. Mean time scales for bond breaking, the early stage of cage escape, and non-Fickian displacement by a fixed amount are analyzed in the repulsive glass, bonded repulsive (attractive) glass, fluid, and dense gel regimes. The theory predicts a strong length-scale-dependent growth of these time scales with attractive force strength at fixed packing fraction, a much weaker slowing down with density at fixed attraction strength, and a strong decoupling of the shorter bond breaking time with the other two time scales that are controlled mainly by perturbed steric caging. All results are in good accord with simulations, and additional testable predictions are made. In conclusion, the classic statistical mechanical projection approximation of replacing all bare attractive and repulsive forces with a single effective force determined by pair structure incurs major errors for describing processes associated with thermally activated escape from transiently localized states.

36 MATERIALS SCIENCE↗

Theory of capillary tension and interfacial dynamics of motility-induced phases

The statistical mechanics of equilibrium interfaces has been well-established for over a half century. In the past decade, a wealth of observations have made increasingly clear that a new perspective is required to describe interfaces arbitrarily far from equilibrium. In this work, beginning from microscopic particle dynamics that break time-reversal symmetry, we derive the linear interfacial dynamics of coexisting motility-induced phases. Doing so allows us to identify the athermal energy scale that excites interfacial fluctuations and the nonequilibrium surface tension that resists these excitations. Our theory identifies that, in contrast to equilibrium fluids, this active surface tension contains contributions arising from nonconservative forces which act to suppress interfacial fluctuations and, crucially, is distinct from the mechanical surface tension of Kirkwood and Buff. Here we find that the interfacial stiffness scales linearly with the intrinsic persistence length of the constituent active particle trajectories, in agreement with simulation data. We demonstrate that at wavelengths much larger than the persistence length, the interface obeys surface-area minimizing Boltzmann statistics with our derived nonequilibrium interfacial stiffness playing a role identical to that of equilibrium systems.

36 MATERIALS SCIENCE↗

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC), a time projection chamber is used as the main tracking detector, which records particle trajectories in a volume of three-dimensional (3D) cylinder. The resulting data are usually very sparse with occupancy around 10.8%. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE), outperforms traditional methods both in compression rate and reconstruction accuracy. BCAE can also utilize the computation power of graphical processing units suitable for deployment in a modern heterogeneous highperformance computing environment. This work introduces two BCAE variants: BCAE++ and BCAE-2D. BCAE++ achieves a 15% better compression ratio and a 77% better reconstruction accuracy measured in mean absolute error compared with BCAE. BCAE-2D treats the radial direction as the channel dimension of an image, resulting in a 3× speedup in compression throughput. In addition, we demonstrate an unbalanced autoencoder with a larger decoder can improve reconstruction accuracy without significantly sacrificing throughput. Lastly, we observe both the BCAE++ and BCAE-2D can benefit more from using half-precision mode in throughput (76 - 79% increase) without loss in reconstruction accuracy. The source code and links to data and pretrained models can be found at https://github.com/BNL-DAQ-LDRD/NeuralCompression_v2

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Theoretical Study of the Single Electron Optical Stochastic Cooling Experiment at the IOTA Facility (Final Technical Report)

The objectives of this proposal were to explore fundamental aspects of radiation from individual and small groups of electrons in the optical stochastic cooling experiment conducted at Fermi National Laboratory's IOTA facility. Professor Swapan Chattopadhyay collaborated directly with the IOTA team on their initial experimental endeavors. Concurrently, a team from Berkeley, including Prof. Wurtele, Dr. Charman, and Dr. Greggory Penn from LBNL, and Prof. Chattapadhyay, pursued a theoretical exploration to identify potential subsequent experiments for IOTA. A wide range of possible experiments were considered, but they do not allow for tests for new quantum mechanical phenomena at the precision level of the current IOTA apparatus. However, the experimentally observed optical stochastic cooling of a single electron in IOTA validated the relevance of the classical electromagnetic field nature of the continuous electron-radiation interaction (as opposed to discrete instantaneous photon emissions and associated 'classical particle trajectory jumps') responsible for cooling and pointed towards innovative methods of experimental techniques to measure 'turn-by-turn' field correlations. Such measurements have the promise of bridging the transition from classical fields building up to discrete quantum transitions and enhance proper theoretical understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A numerical investigation of coal particle modeling for the inlet section of a pressurized oxy-combustion burner

Concerns over climate change have led to numerous efforts to develop low-carbon technologies, and pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in the power industry. Designing an effective burner for such technologies is vital for the development of these and other coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the pressurized oxy-combustor burner is close to or even higher than the maximum limit for commercial CFD codes (e.g., ANSYS FLUENT). At these high particle volume fractions, the interactions among particles, fluid flow and wall need to be re-evaluated. The present computational work is a first step in a systematic analysis of the influence of various parameters, like method of particle release, release location, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In the POC process, pulverized coal is burned under elevated pressure in an O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing Ansys FLUENT commercial sodtware using the Reynolds-Averaged Navier-Stokes (RANS) approach. It is revealed that for this pilot-scale, pressurized burner, velocity profiles in the near-wall region exhibit some anomalies. In order to investigate the influence of particle loading in the near-wall region, particle release location was investigated. The numerical simulations incorporate the coupling between the turbulent flow and the particles. A sensitivity investigation of particle release location found that by tuning the release location, the velocity profile can be consistent with the pure gas flow velocity profile. More importantly, the particle releasing location also affects flame stability. Particle size was also found to have a significant impact on particle trajectory, flame stability and temperature. Finally, Large Eddy Simulations (LES) were performed and compared with the results from two-dimensional RANS.

Li, Lei↗

Impact of particle size and particle-flow-wall coupling on pressurized oxy-combustion in the down-fired burner

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the burner of a pressurized oxy-combustor is close or even higher than the maximum limit that commercial CFD codes (e.g., ANSYS FLUENT) can handle. At this high particle volume fraction, the interactions among particles, fluid flow, and wall need to be re-evaluated. The present computational work is the first step of a systematic analysis of the particle influence, like releasing method, releasing locating, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing ANSYS FLUENT, using Reynolds-averaged Navier-Stokes (RANS) modeling. It is revealed that for this pilot-scale, pressurized burner, velocity profiles of the near-wall region in this POC facility exhibit some discrepancy against the near-wall turbulent flow velocity profile. In order to investigate the particle influence in the near-wall region, particle releasing location will be investigated. Numerical simulation results exhibit the coupling effect of turbulence flow and particles in this case. The particle size also demonstrates a great effect on particle trajectory, then further has an impact on flame stability and temperature.

Li, Lei↗

A Laboratory-driven Multiscale Investigation of X-Ray Induced Mass Loss and Photochemical Evolution in Cosmic Carbon and Silicate Dust

We present the results of an integrated laboratory and modeling investigation into the impact of stellar X-rays on cosmic dust. Carbonaceous grains were prepared in a cooled (< 200 K) supersonic expansion from aromatic molecular precursors, and were later irradiated with 970 eV X-rays. Silicate (enstatite) grains were prepared via laser ablation, thermally annealed, and later irradiated with 500 eV X-rays. Infrared spectra of the 3.4 μm band of the carbon sample prepared with benzene revealed 84% ± 5% band area loss for an X-ray dose of 5.2 x 10 23 eV.cm -2 . Infrared spectra of the 8 -12 μm Si-O band of the silicate sample revealed band area loss up to 63% ± 5% for doses of 2.3 x 10 23 eV.cm -2 . A hybrid Monte Carlo particle trajectory approach was used to model the impact of X-rays and ensuing photoelectrons, Auger and collisionally ionized electrons through the bulk. As a result of x-ray ionization and ensuing Coulomb explosions on surface molecules, the calculated mass loss is 60% for the carbonaceous sample and 46% for the silicate sample, within a factor of 2 of the IR band loss, supporting an X-ray induced mass-loss mechanism. We apply the laboratory X-ray destruction rates to estimate the lifetimes of dust grains in protoplanetary disks surrounding 1 M ⊙ and 0.1 M ⊙ G and M stars. In both cases, X-ray destruction timescales are short (a few million years) at the disk surface, but are found to be much longer than typical disk lifetimes (≳10 Myr) over the disk bulk.

79 ASTRONOMY AND ASTROPHYSICS↗

Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps

In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.

Sane, Sudhanshu↗

Flow matching beyond kinematics: Generating jets with particle identification and trajectory displacement information

We introduce the first generative model trained on the etlass dataset. Our model generates jets at the constituent level, and it is a permutation-equivariant continuous normalizing flow (CNF) trained with the flow matching technique. It is conditioned on the jet type, so that a single model can be used to generate the ten different jet types of etlass. For the first time, we also introduce a generative model that goes beyond the kinematic features of jet constituents. The etlass dataset includes more features, such as particle-ID and track impact parameter, and we demonstrate that our CNF can accurately model all of these additional features as well. Our generative model for etlass expands on the versatility of existing jet generation techniques, enhancing their potential utility in high-energy physics research, and offering a more comprehensive understanding of the generated jets. Published by the American Physical Society 2025

Birk, Joschka (ORCID:0000000219310127)↗

Lagrangian dynamics of particle transport in oral and nasal breathing

Here, we present a large-eddy simulation (LES) of saliva particle transport during normal human breathing through the nose and mouth. The flow of the air–saliva mixture is modeled using an Eulerian LES that is coupled with a Lagrangian particle tracking module to obtain trajectories of saliva particles in a room with stagnant air conditions. The coupled Eulerian–Lagrangian simulation yields novel insights into the intricate dynamics of Lagrangian coherent structures (LCS) and fundamental material lines that emerge from the saliva particles' trajectories during several breathing cycles. Further, we systematically compare the quantitative LCS diagnostics of mouth breathing with those of mouth and nose normal breathing. Analyzing the simulation results of human breathing from the mouth and nose, we show that, soon after the first breathing cycle, saliva particles form a series of roll-up vortex rings that propagate forward. The forward propagation of these vortex rings leads to the formation of an asymmetrical primary forefront vortex. The individual vortex rings continuously propagate forward, merging with the forefront vortex, and ascending along the limb of the leading vortex.

42 ENGINEERING↗

Hyperdiffusion of dust particles in a turbulent tokamak plasma

The effect of plasma turbulence on the trajectories of dust particles is investigated for the first time. The dynamics of dust particles is computed using the ad-hoc developed Dust Injection Simulator code, using a 3D turbulent plasma background computed with the TOKAM3X code. As a result, the evolution of the particle trajectories is governed by the ion drag force, and the shape of the trajectory is set by the Stokes number $St\propto a_d/n_0$, with $a_d$ the dust radius and $n_0$ the density at the separatrix. The plasma turbulence is observed to scatter the dust particles, exhibiting a hyperdiffusive regime in all cases. The amplitude of the turbulent spread of the trajectories $\Delta r^2$ is shown to depend on the ratio $Ku/St$, with $Ku\propto u_{rms}$ the Kubo number and $u_{rms}$ the fluctuation level of the plasma flow. These results are compared with a simple analytical model, predicting $\Delta r^2\propto (Ku/St)^2t^3$, or $\Delta r^2\propto (u_{rms}n_0/a_d)^2t^3$. As the dust is heated by the plasma fluxes, thermionic emission sets the dust charge, originally negative, to slightly positive values. This results in a substantial reduction of the ion drag force through the suppression of its Coulomb scattering component. The dust grain inertia is then no longer negligible, and drives the transition from a hyperdiffusive regime towards a ballistic one.

dust↗

Physicochemical and Molecular Insights into the Boundary Layer and Free Troposphere Aerosol Interactions over the Southern Great Plains

Ambient aerosols’ vertical profiles are critical for evaluating the role of aerosols in atmospheric chemistry and radiative transfer, but limited data on these profiles hinders our ability to fully assess their impact on the Earth's radiative balance. Here, in this study, we investigated the size-, time-, and altitude resolved composition of individual particles and bulk molecular composition of particle samples collected by an uncrewed aerial system–ArcticShark over the Southern Great Plains. Single particle microanalysis shows that, the free tropospheric (FT) samples are dominated (56-66%) by carbonaceous sulfate particles, while boundary layer (BL) samples are dominated (57-74%) by carbonaceous particles. Back trajectory simulations suggest that FT particles are likely influenced by long-range transport and have undergone aqueous-phase processing. Conversely, in-situ size distribution data shows evidence of particle growth in the upper BL and just below the FT. This observation may indicate vertical transport of particles from an elevated aerosol layer in the FT, possibly linked to a new particle formation event. This observation is further supported by high resolution molecular composition data, which reveals particle volatility increasing with increasing size, which aligns with the growth event. This study aids in fundamental understanding of the compositional and molecular specificity of vertically resolved organic aerosols to provide insights into particle size evolution for future atmospheric models.

ArcticShark↗

Hyperdiffusion of dust particles in a turbulent tokamak plasma

In this work, the effect of plasma turbulence on the trajectories of dust particles is investigated for the first time. The dynamics of dust particles is computed using the ad hoc developed Dust Injection Simulator code, using a 3D turbulent plasma background computed with the TOKAM3X code. As a result, the evolution of the particle trajectories is governed by the ion drag force, and the shape of the trajectory is set by the Stokes number St∝a d /n 0 , with a d the dust radius and n 0 the density at the separatrix. The plasma turbulence is observed to scatter the dust particles, exhibiting a hyperdiffusive regime in all cases. The amplitude of the turbulent spread of the trajectories Δr 2 is shown to depend on the ratio Ku/St, with Ku∝u rms the Kubo number and urms the fluctuation level of the plasma flow. These results are compared with a simple analytical model, predicting Δr 2 ∝(Ku/St) 2 t 3 , or Δr 2 ∝(u rms n 0 /a d ) 2 t 3 . As the dust is heated by the plasma fluxes, thermionic emission sets the dust charge, originally negative, to slightly positive values. This results in a substantial reduction of the ion drag force through the suppression of its Coulomb scattering component. The dust grain inertia is then no longer negligible and drives the transition from a hyperdiffusive regime toward a ballistic one.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ion-driven destabilization of a toroidal electron plasma—A 3D3V PIC simulation

Ion-driven destabilization of a toroidal electron plasma in a small aspect ratio axisymmetric toroidal device is reported for A r + ions of different initial density values using a high fidelity 3D3V PIC solver. Stability of a recently discovered quiescent quasi-steady state (QQS) of a toroidal electron plasma obtained from “seed” solution as a result of entropy extremization at zero inertia is addressed in the presence of a small ion population. An initial value (f0) of the ion fraction (f = n i / n e) and the corresponding secondary electrons are “preloaded” into the system after the electron plasma attains a QQS state. This procedure is regarded as a proxy to the conventional production of ions in the experimental devices via impact ionization. The resulting electron plasma exhibits destabilized “center of charge motion” (m = 1) along with higher order harmonics with dominant power in the second harmonic. Gradual loss of ions (and also electrons) is observed resulting in time varying f values. Beyond a certain value of f0 (≥ 0.005), growth in wall probe current is observed, which saturates at later simulation time due to the loss of particles. In conclusion, trajectories of ion particles indicate ion trapping in the potential well, which is qualitatively similar to the ion resonance instability in pure electron plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Guiding centre motion for particles in a ponderomotive magnetostatic end plug

The Hamiltonian dynamics of a single particle in a rotating plasma column, interacting with an magnetic multipole is perturbatively solved for up to second order, using the method of Lie transformations. First, the exact Hamiltonian is expressed in terms of canonical action-angle variables, and then an approximate integrable Hamiltonian is introduced, using another set of actions and angles, which describe the centre of oscillation for the particle. The perturbation introduces an effective ponderomotive potential, which to leading order is positive. At the second order, the pseudopotential consists of a sum of terms of the Miller form, and can have either sign. Additionally, at second order, the ponderomotive interaction introduces a modification to the particle effective mass, when considering the motion along the column axis. It is found that particles can be axially confined by the ponderomotive potentials, but acquire radial excursions which scale as the confining potential. The radial excursions of the particle along its trajectory are investigated, and a condition for the minimal rotation frequency for which the particle remains radially confined is derived. Last, we comment on the changes to the aforementioned solution to the pseudopotentials and particle trajectory in the case of resonant motion, that is, a motion which has the same periodicity as the perturbation.

Rubin, T. (ORCID:0000000164850096)↗

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗

Exploring the elevated water vapor signal associated with the free tropospheric biomass burning plume over the southeast Atlantic Ocean

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol-cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6-7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ~5-6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (~6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

54 ENVIRONMENTAL SCIENCES↗