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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2020

CosTuuM: Polarized Thermal Dust Emission by Magnetically Oriented Spheroidal Grains

We present the new open-source C++-based Python library CosTuuM that can be used to generate infrared absorption and emission coefficients for arbitrary mixtures of spheroidal dust grains that are (partially) aligned with a magnetic field. We outline the algorithms underlying the software, demonstrate the accuracy of our results using benchmarks from literature, and use our tool to investigate some commonly used approximative recipes. We find that the linear polarization fraction for a partially aligned dust grain mixture can be accurately represented by an appropriate linear combination of perfectly aligned grains and grains that are randomly oriented, but that the commonly used picket fence alignment breaks down for short wavelengths. We also find that for a fixed dust grain size, the absorption coefficients and linear polarization fraction for a realistic mixture of grains with various shapes cannot both be accurately represented by a single representative grain with a fixed shape, but that instead an average over an appropriate shape distribution should be used. Insufficient knowledge of an appropriate shape distribution is the main obstacle in obtaining accurate optical properties. CosTuuM is available as a standalone Python library and can be used to generate optical properties to be used in radiative transfer applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Kepler and TESS Observations of PG 1159-035

Abstract PG 1159-035 is the prototype of the PG 1159 hot (pre-)white dwarf pulsators. This important object was observed during the Kepler satellite K2 mission for 69 days in 59 s cadence mode and by the TESS satellite for 25 days in 20 s cadence mode. We present a detailed asteroseismic analysis of those data. We identify a total of 107 frequencies representing 32 ℓ = 1 modes, 27 frequencies representing 12 ℓ = 2 modes, and eight combination frequencies. The combination frequencies and the modes with very high k values represent new detections. The multiplet structure reveals an average splitting of 4.0 ± 0.4 μ Hz for ℓ = 1 and 6.8 ± 0.2 μ Hz for ℓ = 2, indicating a rotation period of 1.4 ± 0.1 days in the region of period formation. In the Fourier transform of the light curve, we find a significant peak at 8.904 ± 0.003 μ Hz suggesting a surface rotation period of 1.299 ± 0.002 days. We also present evidence that the observed periods change on timescales shorter than those predicted by current evolutionary models. Our asteroseismic analysis finds an average period spacing for ℓ = 1 of 21.28 ± 0.02 s. The ℓ = 2 modes have a mean spacing of 12.97 ± 0.4 s. We performed a detailed asteroseismic fit by comparing the observed periods with those of evolutionary models. The best-fit model has T eff = 129, 600 ± 11 100 K, M * = 0.565 ± 0.024 M ⊙ , and log g = 7.41 − 0.54 + 0.38 , within the uncertainties of the spectroscopic determinations. We argue for future improvements in the current models, e.g., on the overshooting in the He-burning stage, as the best-fit model does not predict excitation for all of the pulsations detected in PG 1159-035.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Halted-pendulum Relaxation: Application to White Dwarf Binary Initial Data

Studying compact-star binaries and their mergers is integral to determining progenitors for observable transients. Today, compact-star mergers are typically studied via state-of-the-art computational fluid dynamics codes. One such numerical technique, smoothed particle hydrodynamics (SPH), is frequently chosen for its excellent mass, energy, and momentum conservation. The natural treatment of vacuum and the ability to represent highly irregular morphologies make SPH an excellent tool for the study of compact-star binaries and mergers. For many scenarios, including binary systems, the outcome of simulations is only as accurate as the initial conditions. For SPH, it is essential to ensure that the particles are distributed regularly, representing the initial density profile but without long-range correlations. Particle noise in the form of high-frequency local motion and low-frequency global dynamics must be damped out. Damping the latter can be as computationally intensive as the actual simulation. We discuss a new and straightforward relaxation method, halted-pendulum relaxation (HPR), to remove global oscillation modes of SPH particle configurations. In combination with effective external potentials representing gravitational and orbital forces, we show that HPR has an excellent performance in efficiently relaxing SPH particles to the desired density distribution and removing global oscillation modes. We compare the method to frequently used relaxation approaches and test it on a white dwarf binary model at its Roche-lobe overflow limit. We highlight the importance of our method in achieving accurate initial conditions and its effect on achieving circular orbits and realistic accretion rates when compared with other general relaxation methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Reprocessing Models for the Optical Light Curves of Hypervariable Quasars from the Sloan Digital Sky Survey Reverberation Mapping Project

We explore reprocessing models for a sample of 17 hypervariable quasars, taken from the Sloan Digital Sky Survey Reverberation Mapping project, which all show coordinated optical luminosity hypervariability with amplitudes of factors ≳2 between 2014 and 2020. We develop and apply reprocessing models for quasar light curves in simple geometries that are likely to be representative of quasar inner environments. In addition to the commonly investigated thin-disk model, we include the thick-disk and hemisphere geometries. The thick-disk geometry could, for instance, represent a magnetically elevated disk, whereas the hemisphere model can be interpreted as a first-order approximation for any optically thick out-of-plane material caused by outflows/winds, warped/tilted disks, and so on. Of the 17 quasars in our sample, 11 are best-fitted by a hemisphere geometry, five are classified as thick disks, and both models fail for just one object. We highlight the successes and shortcomings of our thermal reprocessing models in case studies of four quasars that are representative of the sample. While reprocessing is unlikely to explain all of the variability that we observe in quasars, we present our classification scheme as a starting point for revealing the likely geometries of reprocessing for quasars in our sample and hypervariable quasars in general.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Evidence for X-Ray Emission in Excess to the Jet-afterglow Decay 3.5 yr after the Binary Neutron Star Merger GW 170817: A New Emission Component

For the first ~3 yrs after the binary neutron star merger event GW 170817, the radio and X-ray radiation has been dominated by emission from a structured relativistic off-axis jet propagating into a low-density medium with n < 0.01 cm -3 . We report on observational evidence for an excess of X-ray emission at δt > 900 days after the merger. With L x ≈ 5 × 10 38 erg s -1 at 1234 days, the recently detected X-ray emission represents a ≥ 3.2σ (Gaussian equivalent) deviation from the universal post-jet-break model that best fits the multiwavelength afterglow at earlier times. In the context of JetFit afterglow models, current data represent a departure with statistical significance ≥ 3.1σ, depending on the fireball collimation, with the most realistic models showing excesses at the level of ≥ 3.7σ. A lack of detectable 3 GHz radio emission suggests a harder broadband spectrum than the jet afterglow. These properties are consistent with the emergence of a new emission component such as synchrotron radiation from a mildly relativistic shock generated by the expanding merger ejecta, i.e., a kilonova afterglow. In this context, we present a set of ab initio numerical relativity binary neutron star (BNS) merger simulations that show that an X-ray excess supports the presence of a high-velocity tail in the merger ejecta, and argues against the prompt collapse of the merger remnant into a black hole. Radiation from accretion processes on the compact-object remnant represents a viable alternative. Neither a kilonova afterglow nor accretion-powered emission have been observed before, as detections of BNS mergers at this phase of evolution are unprecedented

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Improving Photometric Redshift Estimates with Training Sample Augmentation

Abstract Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy Survey of Space and Time (LSST), so we seek methods to improve the photo- z estimates that arise from nonrepresentative training samples. Spectroscopic training samples for photo- z 's are biased toward redder, brighter galaxies, which also tend to be at lower redshift than the typical galaxy observed by LSST, leading to poor photo- z estimates with outlier fractions nearly 4 times larger than for a representative training sample. In this Letter, we apply the concept of training sample augmentation, where we augment simulated nonrepresentative training samples with simulated galaxies possessing otherwise unrepresented features. When we select simulated galaxies with ( g - z ) color, i -band magnitude, and redshift outside the range of the original training sample, we are able to reduce the outlier fraction of the photo- z estimates for simulated LSST data by nearly 50% and the normalized median absolute deviation (NMAD) by 56%. When compared to a fully representative training sample, augmentation can recover nearly 70% of the degradation in the outlier fraction and 80% of the degradation in NMAD. Training sample augmentation is a simple and effective way to improve training samples for photo- z 's without requiring additional spectroscopic samples.

Moskowitz, Irene (ORCID:0000000222068589)↗
DOE OSTI2021

The Effect of Spark-Plug Heat Dispersal Range and Exhaust Valve Opening Timing on Cold-Start Emissions and Cycle-to-Cycle Variability

The partnership for advancing combustion engines (PACE) is a US Department of Energy consortium involving multiple national laboratories and includes a goal of addressing key efficiency and emission barriers in light-duty engines fueled with a market-representative E10 gasoline. A major pillar of the initiative is the generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster light-off of the three-way catalyst and engine out emissions during that period. In this study, gaseous and soot emissions were measured at a distance representative of the three-way catalyst position downstream of the engine at a 2 bar net indicated mean effective pressure (NIMEP) steady-state operating condition representative of cold-start. The test matrix included sweeps of ignition timing 15 degrees-before to 10 degrees-after top dead center firing (TDCf) across three different spark-plug heat dispersal ranges (HR). Additionally, the effect of varying exhaust valve opening (EVO) timing on combustion stability and emissions was also studied. Results show that the spark plug HR affects the coefficient of variation (COV) of NIMEP under all cold-start conditions, while the impact on emissions was found to be minimal. At very retarded spark timings, colder spark plugs required higher air and fuel flow to maintain the desired 2bar NIMEP load, but the fraction of fuel energy going into the exhaust was found to be similar for all spark plugs. Finally, retarding exhaust valve timings showed a simultaneous reduction in emissions while increasing the fraction of fuel energy being fed into the exhaust. However, engine COV was also observed to increase with retarded exhaust timings.

42 ENGINEERING↗
DOE OSTI2020

Development of aerosol activation in the double-moment Unified Model and evaluation with CLARIFY measurements

Representing the number and mass of cloud and aerosol particles independently in a climate, weather prediction or air quality model is important in order to simulate aerosol direct and indirect effects on radiation balance. Here we introduce the first configuration of the UK Met Office Unified Model in which both cloud and aerosol particles have “double-moment” representations with prognostic number and mass. The GLObal Model of Aerosol Processes (GLOMAP) aerosol microphysics scheme, already used in the Hadley Centre Global Environmental Model version 3 (HadGEM3) climate configuration, is coupled to the Cloud AeroSol Interacting Microphysics (CASIM) cloud microphysics scheme. We demonstrate the performance of the new configuration in high-resolution simulations of a case study defined from the CLARIFY aircraft campaign in 2017 near Ascension Island in the tropical southern Atlantic. We improve the physical basis of the activation scheme by representing the effect of existing cloud droplets on the activation of new aerosol, and we also discuss the effect of unresolved vertical velocities. We show that neglect of these two competing effects in previous studies led to compensating errors but realistic droplet concentrations. While these changes lead only to a modest improvement in model performance, they reinforce our confidence in the ability of the model microphysics code to simulate the aerosol–cloud microphysical interactions it was designed to represent. Capturing these interactions accurately is critical to simulating aerosol effects on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling secondary organic aerosol formation from volatile chemical products

Abstract. Volatile chemical products (VCPs) are commonly used consumer and industrial items that are an important source of anthropogenic emissions. Organic compounds from VCPs evaporate on atmospherically relevant timescales and include many species that are secondary organic aerosol (SOA) precursors. However, the chemistry leading to SOA, particularly that of intermediate-volatility organic compounds (IVOCs), has not been fully represented in regional-scale models such as the Community Multiscale Air Quality (CMAQ) model, which tend to underpredict SOA concentrations in urban areas. Here we develop a model to represent SOA formation from VCP emissions. The model incorporates a new VCP emissions inventory and employs three new classes of emissions: siloxanes, oxygenated IVOCs, and nonoxygenated IVOCs. VCPs are estimated to produce 1.67 µg m−3 of noontime SOA, doubling the current model predictions and reducing the SOA mass concentration bias from −75 % to −58 % when compared to observations in Los Angeles in 2010. While oxygenated and nonoxygenated intermediate-volatility VCP species are emitted in similar quantities, SOA formation is dominated by the nonoxygenated IVOCs. Formaldehyde and SOA show similar relationships to temperature and bias signatures, indicating common sources and/or chemistry. This work suggests that VCPs contribute up to half of anthropogenic SOA in Los Angeles and models must better represent SOA precursors from VCPs to predict the urban enhancement of SOA.

Pennington, Elyse A. (ORCID:0000000317362342)↗
DOE OSTI2023

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

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global nitrogen and sulfur deposition mapping using a measurement–model fusion approach

Abstract. Global reactive nitrogen (N) deposition has more than tripled since 1860 and is expected to remain high due to food production and fossil fuel consumption. Global sulfur emissions have been decreasing worldwide over the last 30 years, but many regions are still experiencing unhealthily high levels of deposition. We update the 2010 global deposition budget for reactive nitrogen and sulfur components with new regional wet deposition measurements from Asia, improving the ensemble results of 11 global chemistry transport models from the second phase of the United Nations Economic Commission for Europe's Task Force on Hemispheric Transport of Air Pollution (HTAP II). The observationally adjusted global N deposition budget is 114.5 Tg N, representing a minor increase of 1 % from the model-only derived values, and the adjusted global sulfur deposition budget is 88.9 Tg S, representing a 6.5 % increase from the modeled values, using an interpolation distance of 2.5∘. Regionally, deposition adjustments can be up to ∼ 73 % for nitrogen and 112 % for sulfur. Our study demonstrates that a global measurement–model fusion approach can improve N and S deposition model estimates at a regional scale, with sufficient availability of observations; however, in large parts of the world, alternative approaches need to be explored. The analysis presented here represents a step forward toward the World Meteorological Organization's goal of global fusion products for accurately mapping harmful air pollution deposition.

Rubin, Hannah J. (ORCID:0000000182226924)↗
DOE OSTI2024

Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry

Abstract. This study aims to enhance the understanding and application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) for the comprehensive characterization of organic nitrogen (ON) compounds in aerosol particles and atmospheric droplets. To achieve this goal, we analyzed 75 N-containing organic compounds, representing a diverse range of ambient non-organonitrate ON (NOON) types, including amines, amides, amino acids, N heterocycles, protein, and humic acids. Our results show that NOON compounds can produce significant levels of NHx+ and NOx+ ion fragments, which are typically recognized as ions representative of inorganic nitrogen species. We also identified the presence of CH2N+ at m/z = 28.0187, an ion fragment rarely quantified in ambient datasets due to substantial interference from N2+. As a result, the utilization of an updated calibration factor of 0.79 is necessary for accurate NOON quantification via the HR-AMS. We also assessed the relative ionization efficiencies (RIEs) for various NOON species and found that the average RIE for NOON compounds (1.52 ± 0.58) aligns with the commonly used default value of 1.40 for organic aerosol. Moreover, through a careful examination of the HR-AMS mass spectral features of various NOON types, we propose fingerprint ion series that can aid the NOON speciation analysis. For instance, the presence of CnH2n+2N+ ions is closely linked with amines, with CH4N+ indicating primary amines, C2H6N+ suggesting secondary amines, and C3H8N+ representing tertiary amines. CnH2nNO+ ions (especially for n values of 1–4) are very likely derived from amides. The co-existence of three ions, C2H4NO2+, C2H3NO+, and CH4NO+, serves as an indicator for the presence of amino acids. Additionally, the presence of CxHyN2+ ions indicates the occurrence of 2N-heterocyclic compounds. Notably, an elevated abundance of NH4+ is a distinct signature for amines and amino acids, as inorganic ammonium salts produce only negligible amounts of NH4+ in the HR-AMS. Finally, we quantified the NOON contents in submicron particles (PM1) and fog water in Fresno, California, and PM1 in New York City (NYC). Our results revealed the substantial presence of amino compounds in both Fresno and NYC aerosols, whereas concurrently collected fog water in Fresno contained a broader range of NOON species, including N-containing aromatic heterocycle (e.g., imidazoles) and amides. These findings highlight the significant potential of employing the widespread HR-AMS measurements of ambient aerosols and droplets to enhance our understanding of the sources, transformation processes, and environmental impacts associated with NOON compounds in the atmosphere.

Ge, Xinlei (ORCID:0000000195316478)↗
DOE OSTI2025

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↗
DOE OSTI2024

Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry

This study aims to enhance the understanding and application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) for comprehensive characterization of organic nitrogen (ON) compounds in aerosol particles and atmospheric droplets. To achieve this, we analyzed seventy-five N-containing organic compounds, representing a diverse range of ambient ON types, including amines, amides, amino acids, N-heterocycles, protein, and humic acids. Our results show that ON compounds can produce significant levels of NH x + and NO x + ion fragments, which are typically recognized as ions representative of inorganic nitrogen species. We also discovered the presence of CH 2 N + at m/z = 28.0187, an ion fragment that is rarely quantified in ambient datasets due to substantial interference from air-related N 2 + . As a result, we determined that an updated calibration factor of 0.79 is necessary to accurately quantify ON content using aerosol mass spectrometry. We also assessed the relative ionization efficiencies (RIEs) for different ON species and found that the average RIE of ON compounds (1.52 ± 0.58) aligns with the commonly used default value of 1.40 for organic aerosol (OA). Moreover, through a careful examination of the HR-AMS mass spectral features of various ON types, we propose fingerprint ion series that can aid the ON speciation analysis. The presence of C n H 2n+2 N + ions is closely linked with amines, with CH 4 N + indicating primary amines, C 2 H 6 N + suggesting secondary amines, and C 3 H 8 N + representing tertiary amines. C n H 2n NO + ions (especially for n values of 1–4) are very likely derived from amides. The co-existence of three ions, C 2 H 4 NO 2 + , C 2 H 3 NO + , and CH 4 NO + , serves as an indicator for the presence of amino acids. Additionally, the presence of C x H y N 2 + ions indicates the occurrence of 2N-heterocyclic compounds. Notably, an elevated abundance of NH 4 + is a distinct signature for amines and amino acids, as inorganic ammonium salts produce only negligible amounts of NH 4 + in HR-AMS. Finally, we quantified the ON contents in submicron particles (PM 1 ) and fog waters in Fresno, California and PM 1 in New York City (NYC). Our results revealed the substantial presence of amino compounds in both Fresno and NYC aerosols, whereas concurrently collected fog waters contained a broader range of ON species, including N-containing aromatic heterocycle (e.g., imidazoles) and amides. These findings highlight the significant potential of employing the widespread HR-AMS measurements of ambient aerosols and droplets to enhance our understanding of the sources, transformation processes, and environmental impacts associated with ON compounds in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Expanding the design space of stratospheric aerosol geoengineering to include precipitation-based objectives and explore trade-offs

Previous climate modeling studies demonstrate the ability of feedback-regulated, stratospheric aerosol geoengineering with injection at multiple independent latitudes to meet multiple simultaneous temperature-based objectives in the presence of anthropogenic climate change. However, the impacts of climate change are not limited to rising temperatures but also include changes in precipitation, loss of sea ice, and many more; knowing how a given geoengineering strategy will affect each of these climate metrics is vital to understanding the limits and trade-offs of geoengineering. Here, we first introduce a new method of visualizing the design space in which desired climate outcomes are represented by 2-D surfaces on a 3-D graph. Surface orientations represent how different injection choices influence that objective, and intersecting surfaces represent objectives which can be met simultaneously. Using this representation as a guide, we present simulations of two new strategies for feedback-regulated aerosol injection, using the Community Earth System Model with the Whole Atmosphere Community Climate Model – CESM1(WACCM). The first simultaneously manages global mean temperature, tropical precipitation centroid, and Arctic sea ice extent, while the second manages global mean precipitation, tropical precipitation centroid, and Arctic sea ice extent. Both simulations control the tropical precipitation centroid to within 5 % of the goal, and the latter controls global mean precipitation to within 1% of the goal. Additionally, the first simulation overcompensates sea ice, while the second undercompensates sea ice; all of these results are consistent with the expectations of our design space model. In addition to showing that precipitation-based climate metrics can be managed using feedback alongside other goals, our simulations validate the utility of our design space visualization in predicting our climate model behavior under a given geoengineering strategy, and together they help illustrate the fundamental limits and trade-offs of stratospheric aerosol geoengineering.

58 GEOSCIENCES↗
DOE OSTI2020

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗
DOE OSTI2020

A new parameterization of ice heterogeneous nucleation coupled to aerosol chemistry in WRF-Chem model version 3.5.1: evaluation through ISDAC measurements

In the Arctic, during polar night and early spring, ice clouds are separated into two leading types of ice clouds (TICs): (1) TIC1 clouds characterized by a large concentration of very small crystals and TIC2 clouds characterized by a low concentration of large ice crystals. Using a suitable parameterization of heterogeneous ice nucleation is essential for properly representing ice clouds in meteorological and climate models and subsequently understanding their interactions with aerosols and radiation. Here, we describe a new parameterization for ice crystal formation by heterogeneous nucleation in water-subsaturated conditions coupled to aerosol chemistry in the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The parameterization is implemented in the Milbrandt and Yau (2005a, b) two-moment cloud microphysics scheme, and we assess how the WRF-Chem model responds to the run-time interaction between chemistry and the new parameterization. Well-documented reference cases provided us with in situ data from the spring 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) over Alaska. Our analysis reveals that the new parameterization clearly improves the representation of the ice water content (IWC) in polluted or unpolluted air masses and shows the poor performance of the reference parameterization in representing ice clouds with low IWC. The new parameterization is able to represent TIC1 and TIC2 microphysical characteristics at the top of the clouds, where heterogenous ice nucleation is most likely occurring, even with the known bias of simulated aerosols by WRF-Chem over the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale

Watersheds are the fundamental Earth surface functioning units that connect the land to aquatic systems. Many watershed-scale models represent hydrological processes but not biogeochemical reactive transport processes. This has limited our capability to understand and predict solute export, water chemistry and quality, and Earth system response to changing climate and anthropogenic conditions. Here we present a recently developed BioRT-Flux-PIHM (BioRT hereafter) v1.0, a watershed-scale biogeochemical reactive transport model. The model augments the previously developed RT-Flux-PIHM that integrates land-surface interactions, surface hydrology, and abiotic geochemical reactions. It enables the simulation of (1) shallow and deep-water partitioning to represent surface runoff, shallow soil water, and deeper groundwater and of (2) biotic processes including plant uptake, soil respiration, and nutrient transformation. The reactive transport part of the code has been verified against the widely used reactive transport code CrunchTope. BioRT-Flux-PIHM v1.0 has recently been applied in multiple watersheds under diverse climate, vegetation, and geological conditions. This paper briefly introduces the governing equations and model structure with a focus on new aspects of the model. It also showcases one hydrology example that simulates shallow and deep-water interactions and two biogeochemical examples relevant to nitrate and dissolved organic carbon (DOC). These examples are illustrated in two simulation modes of complexity. One is the spatially lumped mode (i.e., two land cells connected by one river segment) that focuses on processes and average behavior of a watershed. Another is the spatially distributed mode (i.e., hundreds of cells) that includes details of topography, land cover, and soil properties. Whereas the spatially lumped mode represents averaged properties and processes and temporal variations, the spatially distributed mode can be used to understand the impacts of spatial structure and identify hot spots of biogeochemical reactions. The model can be used to mechanistically understand coupled hydrological and biogeochemical processes under gradients of climate, vegetation, geology, and land use conditions.

54 ENVIRONMENTAL SCIENCES↗