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At least 127 records · Page 7

Electric Grid Simulator For Human Factor Research

The developed code simulates real-time monitor and control for west area of IEEE 118-bus system. The 24-hour load profile for each bus is derived by scaling the system’s rated load in the PSSE sav file according to the California Independent System Operator’s Day-ahead load forecast for May 1, 2024. This simulator performs several critical functions: (1) Calculating time-series power flow every 4 seconds; (2) Updating and dispatching AGC signals every minute; (3) Conducting N-1 contingency analysis every 5 minutes. Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.

Huang, Jianqiao [Idaho National Laboratory (INL), ↗

A Prefire Approach for Probabilistic Assessments of Postfire Debris‐Flow Inundation

Increases in wildfire activity and rainfall intensification are driving more postfire debris flows (PFDF) in many regions around the world. PFDFs are most common in the first postfire year and may even occur before a fire is fully controlled. This underscores the importance of assessing postfire hazards before a fire starts. Evaluation of PFDF hazards prior to fire can help strategize interventions lessening the negative effects of future fires. However, debris-flow runout and inundation analyses are not routine in PFDF hazard assessments, partially due to time constraints and substantial uncertainties in boundary conditions. Here, we propose a prefire PFDF inundation assessment framework using a debris-flow runout model based on the Herschel-Bulkley (HB) rheology (HEC-RAS v6.1). We constrain model inputs and parameters using Bayesian posterior analysis, rainfall-runoff simulations, and a debris-flow volume model. We use observations from recent PFDF incidents in northern Arizona, USA, to calibrate model components and then apply our prefire inundation assessment framework in a nearby unburned area. Specifically, we (a) identify yield stress as the most influential factor on inundation extent and arrival time in a HB model, (b) establish posterior distributions for model parameters suitable for forward modeling by leveraging uncertainties in field observations, and (c) implement a predictive forward analysis in an area that has not burned recently to evaluate PFDF inundation under several future fire scenarios. This study improves our ability to assess postfire debris-flow hazards before a fire begins and provides guidance for future applications of single-phase rheological models when assessing PFDF hazards.

54 ENVIRONMENTAL SCIENCES↗

A Prefire Approach for Probabilistic Assessments of Postfire Debris-Flow Inundation

Increases in wildfire activity and rainfall intensification are driving more postfire debris flows (PFDF) in many regions around the world. PFDFs are most common in the first postfire year and may even occur before a fire is fully controlled. This underscores the importance of assessing postfire hazards before a fire starts. Evaluation of PFDF hazards prior to fire can help strategize interventions lessening the negative effects of future fires. However, debris-flow runout and inundation analyses are not routine in PFDF hazard assessments, partially due to time constraints and substantial uncertainties in boundary conditions. Here, we propose a prefire PFDF inundation assessment framework using a debris-flow runout model based on the Herschel-Bulkley (HB) rheology (HEC-RAS v6.1). We constrain model inputs and parameters using Bayesian posterior analysis, rainfall-runoff simulations, and a debris-flow volume model. We use observations from recent PFDF incidents in northern Arizona, USA, to calibrate model components and then apply our prefire inundation assessment framework in a nearby unburned area. Specifically, we (a) identify yield stress as the most influential factor on inundation extent and arrival time in a HB model, (b) establish posterior distributions for model parameters suitable for forward modeling by leveraging uncertainties in field observations, and (c) implement a predictive forward analysis in an area that has not burned recently to evaluate PFDF inundation under several future fire scenarios. This study improves our ability to assess postfire debris-flow hazards before a fire begins and provides guidance for future applications of single-phase rheological models when assessing PFDF hazards.

54 ENVIRONMENTAL SCIENCES↗

Reconciling calculations and measurements of inverse bremsstrahlung absorption

It was recently shown that the use of Coulomb logarithms appropriate for bremsstrahlung radiation (rather than transport processes) along with corrections for the Langdon effect and ion screening reproduced measurements of collisional absorption in well-characterized underdense plasmas [D. Turnbull et al., Phys. Rev. Lett. 130, 145103 (2023)]. However, it was recognized at the time that the use of the standard absorption-reduction factor from Langdon's seminal paper was inconsistent with the use of Coulomb logarithms that are thermally averaged over a Maxwellian electron-velocity distribution function. A more accurate approach would be to average over the expected super-Gaussian distribution function while accounting for the Gaunt factor's velocity dependence, which somewhat mitigates the Langdon effect; however, at that time, this theory matched the data less well. This conflict is now eliminated with the additional insight that the ionization state of our mid-Z ion species (when present) was lower than had been assumed, as evidenced by the Thomson-scattering data and time-dependent Cretin simulations. We are now able to show that an improved treatment of the Langdon effect provides the best match to data. Otherwise, the prior conclusions remain unchanged. We also show an example of the substantial expected impact to the absorption rate in calculations of indirect-drive hohlraums.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling of Inductive Constant Power Load for Electromagnetic-Transient Simulations-Part II

This paper improves the dynamic constant power (CP) load model that was published in Part I, which is appropriate for electromagnetic-transient (EMT). The improved model conserves all features of its predecessor. For instance, it maintains a fixed power consumption (both active and reactive parts) and a fixed power factor for loads that are predominantly inductive. Furthermore, as the proposed model is a time-dependent system, it is applicable to both sinusoidal and non-sinusoidal case studies. However, the previous model cannot be easily integrated with numeric solvers because it simulated load data over one cycle all together, not sequentially in a time-step manner, due to the limitation involved with the power factor. The improved version, on the contrary, allows the load to be simulated at every time step, which would facilitate its integration with numeric solvers. The model's validity is confirmed by comparing its response with data that is synthesized from constant impedance load, and the result is satisfactory.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Particle_hygroscopicity_growth_factor_HFIMS_TRACER_2022_HOUSTON_IOP

This dataset contains high-temporal-resolution measurements of hygroscopic growth factors (GF), and instrument diagnostic/environmental parameters collected during the TRACER campaign using a coupled Differential Mobility Analyzer (DMA) and Fast Integrated Mobility Spectrometer (FIMS) system (HFIMS). The dataset consists of 49,645 time steps and covers 20 discrete growth factor bins (FIMS_GFbinc). The primary data product is the Probability Density Function (FIMS_cPDF), which characterizes aerosol hygroscopic growth behavior under controlled relative humidity conditions. Instrument operational parameters, including flow temperatures, relative humidities, pressures, and counts for both DMA and FIMS, are provided for quality assurance.

DMA_Dp_mean↗

Accuracy of kinetic equilibrium reconstruction of NSTX and NSTX-U plasmas and its impact on the transport and stability analysis

An accurate magnetohydrodynamic (MHD) equilibrium reconstruction is an essential starting point for stability and transport plasma analysis. Herein this work describes an approach for obtaining kinetic equilibrium reconstructions using the OMFIT framework, which has been applied for the first time to spherical tokamak data from NSTX and NSTX-U. The EFIT equilibrium solver is integrated with experimental data analysis procedures and subsequent TRANSP transport simulations to enhance the accuracy of the reconstruction, in particular, at the edge region, by adding constraints on the total pressure and current density profiles, based on the transport code solution. The accuracy of the equilibrium reconstruction depends on the uncertainty and number of constraints, as well as the choice of basis functions to represent the pressure and current density profiles. Improved fidelity of the equilibrium reconstruction is demonstrated by reducing the variability of the magnetic axis and boundary locations from several centimeters, for reconstructions based on magnetic and experimental pressure constraints, to only several millimeters, for kinetic reconstructions based on transport code constraints, when different representations of basis functions were tested. The variability of the safety factor on axis was reduced ten times in the same sensitivity study. The accuracy of the equilibrium reconstruction and subsequent mapping of the experimental kinetic profile data have a significant impact on the trapped gyro Landau fluid and linear CGYRO turbulence simulations, which predict different spectra of unstable modes and turbulent fluxes for cases with different numbers of constraints in the equilibrium reconstruction. Conversely, the stability analysis performed using the GATO code shows plasmas that are stable to n = 1 MHD modes in both equilibria using magnetic and experimental pressure constraints as well as the transport code constrained equilibrium. However, a scan of parameters away from these conditions shows considerable deviation in the threshold of unstable modes between these reconstructions. Therefore, for reliable plasma analysis and use in turbulence and stability calculations, a high-fidelity equilibrium reconstruction with accurate kinetic constraints based on transport code solutions is necessary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessment of NuScale SMR Steam Heat Augmentation for Chemical Plant Decarbonization

Nearly 50% of the total energy consumed by the industrial sector in the United States is used to produce process steam with natural gas and coal-fired boilers1 . This project conducts a technoeconomic assessment of a NuScale Small Modular Reactor (SMR) coupled with a chemical plant as an Integrated Energy System (IES) where nuclear produces steam and electric power to meet the requirements of a large chemical plant. In a 2020 study, ORNL evaluated the feasibility of using advanced SMRs, including the NuScale design, to supply energy to the Eastman Chemical Plant. However, since that report was published, NuScale received NRC approval for its uprated 77 MWe design with 56% more power and has also introduced a high-temperature, high pressure, steam heat-augmentation system, a key focus of the new study. The new study also benefits from revised capital costs, a 10-day refueling outage time, reduced plant staffing, higher capacity factors, and a site boundary Emergency Planning Zone methodology. The study consists of a techno-economic assessment of two possible energy sources (nuclear and natural gas) in a number of steam and power generation configurations (NuScale Power Modules (NPMs), boilers and combinations of both) to satisfy the steam and power demand with the most reliable and cost competitive system. A total of 2,947.3 klb/hr of steam and 72.5 MWe of electricity are required for the demonstration case. A range of scenarios and solutions are explored, from a 12-NPM plant (3,000 MWth)—with excess capacity and redundancy, capable of supplying a significant amount of extra power to the grid—to a 4-NPM (1,000 MWth) plant—supplemented with existing boilers or grid power for redundancy. The study uses historical steam and power data from a chemical plant and examines the sensitivity to natural gas and grid power cost variations. Scenarios with up to two times gas and electricity costs were considered. Profitability in a 60-year time horizon was analyzed, consistent with NuScale’s design life specification. A steady-state site integration and reliability analysis was performed, and trade-offs were identified.

20 FOSSIL-FUELED POWER PLANTS↗

Factors influencing recent trends in retail electricity prices in the United States

This study analyzes the primary drivers of recent state-level trends in U.S. retail electricity prices. We summarize pricing trends, explore descriptive relationships, and employ regression models to quantify the influence of various factors. Although the recent national rise in retail prices has largely tracked inflation, state-level trends vary widely. We identify a number of factors that explain trends in subsets of states. States with the greatest price increases typically exhibited shrinking customer loads—partially linked to growth in net metered behind-the-meter solar—and had renewables portfolio standards (RPS) in concert with relatively costly incremental renewable energy supplies. By contrast, recent utility-scale wind and solar deployment that occurred outside RPS programs (but that benefited from tax incentives) had no discernible impact on increased retail prices. Hurricanes, storms and wildfires also contributed to sizable price increases in some states, most notably in California, where wildfire risk mitigation and liability insurance were major cost drivers. Fluctuations in natural gas prices—particularly following the onset of the Ukraine-Russia war—further contributed to sharp price increases through 2022–2023 in many states, with moderation in 2024. The relative influence of these factors varies across states and over time, and relationships may change in the future. Nonetheless, the findings underscore the diverse set of price determinants and highlight the need for continued research to inform effective policy and ensure customer affordability.

Customer load↗

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗

The Scientific Case for Concurrent Neutron and X-ray Scattering and Spectroscopy

The interrogation of materials with X-rays or neutrons to determine the structure, energetics, and dynamics of materials is fundamental to advancing materials' physical and chemical science and developing innovative material technologies. A transcending challenge in developing novel materials is that progress hinges on understanding the structure and dynamics across multiple time and length scales in complex materials that feature multiple components, interfaces, and compositions. Despite the ever-growing demands on materials’ characterization, existing approaches are almost exclusively based on isolated X-ray or neutron scattering, i.e., an approach commensurate with the more narrowly defined needs of fifty years ago. A three-day workshop sponsored by the U.S. National Science Foundation (NSF) analyzed the demand for concurrent neutron and X-ray (NeX) experiments. It was held at the Spring Hill Suites, San Jose, California, from June 2 to 4, 2022. In this workshop, 70 national and international experts ascertained the crucial need to establish NeX capabilities to advance the science of complex materials and systems in the US. Here, we illustrate the need for NeX scattering and spectroscopy experiments by showcasing examples that span areas as diverse as biomaterials, energy science, soft matter, and nanomaterials. To provide NeX capability will require new instrumentation that enables concurrent experiments. Affected areas include chemistry, soft matter, quantum materials, pure and applied chemistry, bioscience, geoscience, and applied materials. NeX benefits research outcomes due to the complementarity of the two techniques, which is essential for better model refinement. While joint refinement of data from separate neutron and X-ray experiments is critical to avoid ambiguities, especially in multiphase-multicomponent materials, concurrent experiments overcome scientific and technical barriers associated with single measurements, separated by location and, thus, time. Among all the examples, these factors introduce uncertainties in the results that complicate data analysis. [1,2] [3] While models are strongly sample-dependent, the principles of joint refinement are generally applicable to these disciplines, including the development of advanced parameterization, modeling, and analysis techniques that also consider the temporal and spatial resolutions of the two methods, leading to unambiguous data interpretation. Solutions for technical barriers must be found to realize NeX experiments, including developing robust sample environments that meet the optical requirements of neutrons and X-rays.

36 MATERIALS SCIENCE↗

Fiscal Year 2024 Software Quality Assurance Activities for the ARC Software

The continued goal of the ARC SQA project in the Advanced Reactor Technologies program of DOE is to resolve the QA gaps for the ARC software that limit, or prevent, commercialization of the software for industry users. This project started in earnest in fiscal year 2023 which saw the entire code system moved from a SVN repository to a GitLab repository and an associated software quality assurance plan (SQAP) developed and ratified. Most of the QA gaps in the ARC software were identified in collaboration with industry partners and work begin in fiscal year 2023 and continued in 2024. The primary documentation that is missing includes user manuals, user guides, software verification reports, and code coverage assessments. The SUMMAR manual was completed this fiscal year and work was started on creating manuals for SE2ANL, SE2RCT, and DASSH. Software verification work was carried out for DIF3D and REBUS in a previous program and the current fiscal year saw the completion of software verification reports for GAMSOR, GAMSRC, VARPOW, EvaluateFlux, and SUMMAR. The goal for the next fiscal year is to complete the PERSENT software verification work and begin planning the software verification work for DASSH, SE2ANL, and SE2RCT. The code coverage reports for DIF3D and MC2-3 were completed in the previous fiscal year and the goal is to generate code coverage reports for REBUS, GAMSOR, PERSENT, and DASSH in the coming fiscal year. A considerable amount of effort was spent in the current fiscal year working on the continuous integration capability for automated regression testing in GitLab. The first version of the testing was created in the previous fiscal year and applied to DIF3D and its utility programs. That testing was extended this year to cover GAMSOR, REBUS, and PERSENT. To accomplish this, the first version of the new testing methodology had to be updated to make a single output checking methodology viable for all of the ARC software. This will result in a single document to detail the automated regression testing methodology and minor documents to detail the tolerance settings that have been applied to the output for each ARC code. The previous methodology put into place with SVN would have required a separate document for each ARC code to detail the output checking methodology and the tolerance settings for the output from each code. Because some of our industry partners are providing funds to add new capabilities to the ARC software to meet their needs, all of which must be reviewed and approved by the SQA program funded by this project, a summary of that development work is detailed in this report. Overall progress on resolving the QA gaps has been good this year with the most impactful improvement for our industry partners in capability being the creation of a threaded version of DIF3D-VARIANT that allows the DIF3D, REBUS, and GAMSOR run times to be reduced by a factor of 4-6. The most impactful QA gap that was resolved was the software verification of GAMSRC and VARPOW.

97 MATHEMATICS AND COMPUTING↗

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗

Mechanical and thermal behavior of additively manufactured Invar 36 using a laser hot wire hybrid DED process

Invar 36 alloy is a material of high interest in the composite tooling sector due to its low coefficient of thermal expansion. Current production of Invar 36 tooling using traditional manufacturing such as casting and forging is associated with long lead times due to a multitude of factors such as labor and component shortages, high material costs, foreign competition, and supply chain issues. An attractive alternate process is the use of an integrated 5-axis CNC hybrid Laser Hot Wire Deposition System (LHWD) for manufacturing invar molds. Here, the hybrid process provides a combination of the additive and subtractive technologies resulting in a synergistic platform for producing and repairing structures and molds. The main novelty and goal of this work is to study the properties of Invar deposited by a LHWD and to provide guidelines for the manufacture of parts using this process. In this study, the thermal expansion behavior of the manufactured specimens has been analyzed and related to its printing parameters and direction. Multiple specimens were extracted for mechanical, dilatometry and metallographic testing. A thermal IR recording of the printing process was also carried out to observe the thermal history of the produced parts to establish thermal influence on performance-property-processing relationship. The results of these tests show the advantage of LHWD technology for the manufacture of Invar alloy parts, as it presents similar thermal expansion behavior as those commercially available with minimal presence of precipitates and no macrostructural failures such as pores, cracks and lacks of fusion.

36 MATERIALS SCIENCE↗

Axion dark matter search with a photonic bandgap cavity haloscope and dielectric tuning rod over 10.25-10.45 GHz

We report the development of a new widely tunable cavity and demonstrate its use in a search for dark matter axions. We achieve unloaded quality factors above $10^{5}$, roughly $25\times$ larger than a bare copper cavity at the same frequency, using concentric sapphire shells to reduce Ohmic losses on the cavity barrel. A rotating sapphire rod tunes our cavity mode over the $10.1-11.7$ GHz range, approximately $16\%$ of its resonant frequency. Using an amplified receiver chain, we demonstrate sensitivity to new axion parameter space by tuning the cavity over the $200$ MHz range between $10.25-10.45$ GHz (42.4 - 43.2, $μ$eV) to constrain the axion-to-photon coupling to $|g_{aγγ}|$$\leq$ 1 $\times$$10^{-12}$${GeV}^{-1}$. This cavity can scan its tuning range about $9$ times faster compared to a bare copper cavity when paired with a photon counting device, laying the groundwork for a definitive search for the QCD axion over $10.1-11.7$ GHz.

Lynn, Morgan [Chicago U.]↗

Mechanism of Molecular Polariton Decoherence in the Collective Light–Matter Couplings Regime

Molecular polaritons, the hybridization of electronic states in molecules with photonic excitation inside a cavity, play an important role in fundamental quantum science and technology. Understanding the decoherence mechanism of molecular polaritons is among the most significant fundamental questions. We theoretically demonstrate that hybridizing many molecular excitons in a cavity protects the overall quantum coherence from phononinduced decoherence. The polariton coherence time can be prolonged up to 100 fs with a realistic collective Rabi splitting and quality factor at room temperature, compared to the typical electronic coherence time which is around 15 fs. Our numerically exact simulations and analytic theory suggest that the dominant decoherence mechanism is the population transfer from the upper polariton state to the dark state manifold. Increasing the collective coupling strength will increase the energy gap between these two sets of states and thus prolong the coherence lifetime. We further derived valuable scaling relations that directly indicate how polariton coherence depends on the number of molecules, Rabi splittings, and light–matter detunings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

16 O + 16 O fusion at sub-coulomb energies

A simple optical model (OPM) method using non-monotonic (NM) potentials characterized by a repulsive core from the microscopic theory of the Pauli-led energy-density functional (EDF) has been developed to investigate the 16 O + 16 O fusion at sub-Coulomb energies relevant to the oxygen burning. Here, the study involves the analysis of the experimental fusion cross-section (FCS) data in energy range 6.92 ≤ E cm ≤ 13.83 MeV, which includes the Coulomb barrier region E cm = 10.0–11.92 MeV. Apart from an excellent description of the existing FCS data in the studied energy range, the associated hindrance, characterized by the S-factor reaching a maximum and then gradually falling off at lower energies, so far suggested empirically for the system, is reproduced down to 4 MeV for the first time in the simple OPM. An S-factor maximum of S 0 = 3.15 × 10 25 MeV.b at E 0 = 7.14 MeV is observed with T ≃ 2.6 GK, which conforms to the values reported for quiescent and explosive burning. Our reaction rate, deduced from the NM potential, compares well with the Caughlan and Fowler data. Dominant partial waves implicit in the observed maximum S-factor in the studied Gamow range are also explored. Our present findings, with the success of NM potentials, suggest that the nucleus–nucleus potential is non-monotonic.

16O+16O↗

Field intercomparison of ice nucleation measurements: the Fifth International Workshop on Ice Nucleation Phase 3 (FIN-03)

Abstract. The third phase of the Fifth International Ice Nucleation Workshop (FIN-03) was conducted at the Storm Peak Laboratory in Steamboat Springs, Colorado, in September 2015 to facilitate the intercomparison of instruments measuring ice-nucleating particles (INPs) in the field. Instruments included two online and four offline measurement systems for INPs, which are a subset of those utilized in the laboratory study that comprised the second phase of FIN (FIN-02). The composition of the total aerosols was characterized using the Particle Analysis by Laser Mass Spectrometry (PALMS) and Wideband Integrated Bioaerosol Sensor (WIBS) instruments, and aerosol size distributions were measured by a laser aerosol spectrometer (LAS). The dominant total particle compositions present during FIN-03 were composed of sulfates, organic compounds, and nitrates, as well as particles derived from biomass burning. Mineral-dust-containing particles were ubiquitous throughout and represented 67 % of supermicron particles. Total WIBS fluorescing particle concentrations for particles with diameters of > 0.5 µm were 0.04 ± 0.02 cm−3 (0.1 cm−3 highest; 0.02 cm−3 lowest), typical of the warm season in this region and representing ≈ 9 % of all particles in this size range as a campaign average. The primary focus of FIN-03 was the measurement of INP concentrations via immersion freezing at temperatures > −33 °C. Additionally, some measurements were made in the deposition nucleation regime at these same temperatures, representing one of the first efforts to include both mechanisms within a field campaign. INP concentrations via immersion freezing agreed within factors ranging from nearly 1 to 5 times on average between matched (time and temperature) measurements, and disagreements only rarely exceeded 1 order of magnitude for sampling times coordinated to within 3 h. Comparisons were restricted to temperatures lower than −15 °C due to the limits of detection related to sample volumes and very low INP concentrations. Outliers of up to 2 orders of magnitude occurred between −25 and −18 °C; a better agreement was seen at higher and lower temperatures. Although the 5–10 factor agreement of INP measurements found in FIN-03 aligned with the results of the FIN-02 laboratory comparison phase, giving confidence in progress of this measurement field, this level of agreement still equates to temperature uncertainties of 3.5 to 5 °C that may not be sufficient for numerical cloud modeling applications that utilize INP information. INP activity in the immersion-freezing mode was generally found to be an order of magnitude or more, making it more efficient than in the deposition regime at 95 %–99 % water relative humidity, although this limited data set should be augmented in future efforts. To contextualize the study results, an assessment was made of the composition of INPs during the late-summer to early-fall period of this study inferred through comparison to existing ice nucleation parameterizations and through measurement of the influence of thermal and organic carbon digestion treatments on immersion-freezing ice nucleation activity. Consistent with other studies in continental regions, biological INPs dominated at temperatures of > −20 °C and sometimes colder, while arable dust-like or other organic-influenced INPs were inferred to dominate below −20 °C.

54 ENVIRONMENTAL SCIENCES↗