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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structures of vertebrate R2 retrotransposon complexes during target-primed reverse transcription and after second-strand nicking

R2 retrotransposons are site-specific eukaryotic non–long terminal repeat retrotransposons that copy and paste into gene loci encoding ribosomal RNAs. Recently, we demonstrated that avian A-clade R2 proteins achieve efficient and precise insertion of transgenes into their native safe-harbor loci in human cells. The features of A-clade R2 proteins that support gene insertion are not well characterized. Here, we report high-resolution cryo–electron microscopy structures of two vertebrate A-clade R2 proteins at the initiation of target-primed reverse transcription and after cDNA synthesis and second-strand nicking. Using biochemical and cellular assays, we illuminate the basis for high selectivity of template use and unique roles for each of the three zinc-finger domains in nucleic acid recognition. Reverse transcriptase active site architecture is reinforced by an unanticipated insertion motif specific to vertebrate A-clade R2 proteins. Our work provides the first insights into A-clade R2 protein structure during gene insertion and may enable future improvement and adaptation of R2-based systems for precise transgene insertion.

Science & Technology - Other Topics↗
DOE OSTI2022

Studsvik R2 materials test reactor Ad Hoc depletion strategy for the derivation of the fuel isotopic composition of the MPCMIV benchmark

The Ad Hoc Depletion Strategy elaborated by the NINE company, developed in support of the organization of the MPCMIV (Multi-physics Pellet Cladding Mechanical Interaction Validation) benchmark input and output specifications, is presented. This work aims at illustrating the strategy itself and then showing the results obtained with its application over the Studsvik R2 Testing Reactor, which is analyzed in the benchmark. The objective of the application of the strategy is to compute the fuel elements isotopic compositions at the beginning of some core loadings of interest for the benchmark. To this objective, it is necessary to implement first the simulation model of the three single assembly types and perform the infinite lattice depletions, then, to build the full core model and to perform the simulation of the core cycle. All the models and simulations were carried out with the use of the Monte Carlo particle transport code Serpent 2. Finally, the simulations results are assessed against Studsvik isotopic compositions of the fuel elements discharged from the R2 Reactor at the end of the core loading. Several assumptions were necessary during all the steps of the strategy, to overcome the lack of information regarding the core management. For this reason, the solution found at the end of the current analysis may not be completely optimized and further improvements regarding the model assumptions will be tested in a future work. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Structure of a ribonucleotide reductase R2 protein radical

Aerobic ribonucleotide reductases (RNRs) initiate synthesis of DNA building blocks by generating a free radical within the R2 subunit; the radical is subsequently shuttled to the catalytic R1 subunit through proton-coupled electron transfer (PCET). Here we present a high-resolution room temperature structure of the class Ie R2 protein radical captured by x-ray free electron laser serial femtosecond crystallography. The structure reveals conformational reorganization to shield the radical and connect it to the translocation path, with structural changes propagating to the surface where the protein interacts with the catalytic R1 subunit. Restructuring of the hydrogen bond network, including a notably short O–O interaction of 2.41 angstroms, likely tunes and gates the radical during PCET. These structural results help explain radical handling and mobilization in RNR and have general implications for radical transfer in proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Plot-level rapid screening for photosynthetic parameters using proximal hyperspectral imaging

Abstract Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (~2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible near infra-red (VNIR) (400–900 nm) hyperspectral camera, we predict maximum carboxylation rate of Rubisco (Vc,max, R2=0.79) maximum electron transport rate in given conditions (J1800, R2=0.59), maximal light-saturated photosynthesis (Pmax, R2=0.54), chlorophyll content (R2=0.87), the Chl a/b ratio (R2=0.63), carbon content (R2=0.47), and nitrogen content (R2=0.49). Model predictions did not improve when using two cameras spanning 400–1800 nm, suggesting a robust, widely applicable and more ‘cost-effective’ pipeline requiring only a single VNIR camera. The analysis pipeline and methods can be used in any cropping system with modified species-specific PLSR analysis to offer a high-throughput field phenotyping screening for germplasm with improved photosynthetic performance in field trials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Simulating measurable ecosystem carbon and nitrogen dynamics with the mechanistically defined MEMS 2.0 model

Abstract. For decades, predominant soil biogeochemical models have used conceptual soil organic matter (SOM) pools and only simulated them to a shallow depth in soil. Efforts to overcome these limitations have prompted the development of the new generation SOM models, including MEMS 1.0, which represents measurable biophysical SOM fractions, over the entire root zone, and embodies recent understanding of the processes that govern SOM dynamics. Here we present the result of continued development of the MEMS model, version 2.0. MEMS 2.0 is a full ecosystem model with modules simulating plant growth with above- and belowground inputs, soil water and temperature by layer, decomposition of plant inputs and SOM, and mineralization and immobilization of nitrogen (N). The model simulates two commonly measured SOM pools – particulate and mineral-associated organic matter (POM and MAOM, respectively). We present results of calibration and validation of the model with several grassland sites in the US. MEMS 2.0 generally captured the soil carbon (C) stocks (R2 of 0.89 and 0.6 for calibration and validation, respectively) and their distributions between POM and MAOM throughout the entire soil profile. The simulated soil N matches measurements but with lower accuracy (R2 of 0.73 and 0.31 for calibration and validation of total N in SOM, respectively) than for soil C. Simulated soil water and temperature were compared with measurements, and the accuracy is comparable to the other commonly used models. The seasonal variation in gross primary production (GPP; R2 = 0.83), ecosystem respiration (ER; R2 = 0.89), net ecosystem exchange (NEE; R2 = 0.67), and evapotranspiration (ET; R2 = 0.71) was well captured by the model. We will further develop the model to represent forest and agricultural systems and improve it to incorporate new understanding of SOM decomposition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mechanical Properties of Permanent Foaming Fixatives for Deactivation and Decommissioning Activities

DOE-EM have identified an operational requirement for a fixative that can immobilize and/or encapsulate residual contamination in 3D void volumes (pipes, gloveboxes, waste containers, etc.) during D and D activities. Failure to safely and effectively immobilize residual contamination can: Put workers at risk, Contaminate the public and environment, Drive up operational costs. Commercial-off-the-shelf (COTS) polyurethane (PU) foams is one possible solution and is currently being investigated in collaboration with Savannah River National Lab (SRNL). Mechanical property testing will dictate how well PU foams can withstand physical stressors outlined in safety documents while immobilizing residual contamination. Results can provide a performance criteria for Section 5 of ASTM E3191: Standard Specification for Permanent Foaming Fixatives Used to Mitigate Spread of Radioactive Contamination. Polyurethanes consists of repeating units of urethanes which are produced from an exothermic reaction between a polyol (an alcohol with two or more hydroxyl groups in a molecule) and an isocyanate [2]. PUs consists of 3D cells that are formed by a blowing agent which is normally water. Water interacting with the isocyanate creates carbon dioxide and urea which contributes to cells' growth and expansion. The cross-linking between the polyol and isocyanate solidify the cell faces and walls. Micro scale properties that can influence mechanical properties include: Relative density (ratio between density of cellular material and density of the solid of which the cell walls are made of). Cells connectivity between edges and faces, and number of cells contact neighbors [3]. Whether a foam is open-celled or closed-celled. Closed-celled foams have a thin membrane that encloses each cell which can contribute to the stiffness of the foam. Incorporating fillers in the PU matrix like carbon-based nanoparticles in the form of expandable graphite (EG) can increase the thermal and mechanical performance [4]. When exposed to heat, EG produces a char layer that prevents heat and oxygen transfer which is known as intumescing. Mechanical performance is dependent on amount of EG loading since the cell sizes are linearly dependent on it. Overall, the rigid foams (I-R2) proved superior. SEM Analysis: I-R2 had the most consistent spherical sizes (average cell diameter: 489 μm), which enhance the relative density the most [5]. Tensile Testing Results: I-R2 experienced the largest breaking load (103.65 lbf) and stress (289.42 psi). I-R2 also had a higher Young's Modulus compared to R1 (2.99 ksi to 2.09 ksi). Compression Testing Results: I-R2 had the highest stress at 80% deflection (360.67 psi), load (1387.48 lbf) and modulus (3.92 ksi)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Rapid prediction of fuel research octane number and octane sensitivity using the AFIDA constant-volume combustion chamber

Current research octane number (RON) and motor octane number (MON) gasoline performance characterization techniques use dated, complex engine testing methodology and limit researchers’ ability to easily characterize small volumes of experimental fuels. A novel methodology is presented that correlates measured ignition delay (ID) time to RON in an Advanced Fuel Ignition Delay Analyzer (AFIDA) constant-volume combustion chamber device at a single pressure/temperature condition, with an r2 of 0.99 and standard error (SE) of 1.0. The correlation of the slope of the ID time between two additional temperature points to octane sensitivity (S) produces an r2 of 0.97 and SE of 0.69; however, fuels with S>12 are indistinguishable. These results are based on methodology calibration using 31 primary and toluene reference fuels containing 0%-40% ethanol with RON values ranging from 85 to 113. Validation of these methods using a 102-sample fuel matrix spanning an array of base fuels and additive chemistry designed to test the robust applicability of the method, along with pump gasoline and high-octane surrogate blend samples, demonstrates an r2 of 0.94 and SE of 1.3 for the RON correlation over all samples, whereas the equivalent S correlation produces an r2 of 0.78 and SE of 1.2 by excluding two additives, 3-pentanone and diisobutylene, which displayed poor S correlation results. This novel AFIDA analysis method can be performed in 1 h and with 40 mL of fuel, offering significant improvements in time and volume requirements over traditional techniques.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Transformation of an Embedded Five-Membered Ring in Polycyclic Aromatic Hydrocarbons via the Hydrogen-Abstraction–Acetylene-Addition Mechanism: A Theoretical Study

Five-membered rings are constituents of many polycyclic aromatic hydrocarbons (PAHs) and their presence on the edges of large PAHs has been repeatedly observed experimentally. However, modern kinetic combustion models often do not consider the growth of PAHs through the transformation of the five-membered rings. Here, in connection with the above, we carried out a theoretical study of the mechanism of Hydrogen-Abstraction-aCetylene-Addition (HACA) transformation of an embedded five-membered ring on the armchair PAH edge to a six-membered ring, considering cyclopenta[d,e,f]phenanthrene (4,5-methylenephenanthrene) as a prototype system for this process. The potential energy surface for the reactions of cyclopenta[d,e,f]phenanthrenyl radicals produced by direct H abstractions from cyclopenta[d,e,f]phenanthrene with acetylene has been compiled at the G3(MP2,CC)//B3LYP/6-311G(d,p) level of theory including zero-point vibrational energy corrections. The computed energies and molecular parameters were then used to solve the Rice-Ramsperger-Kassel-Marcus Master Equation (RRKM-ME) in order to calculate reaction rate at various pressures and temperatures, which were fitted to modified Arrhenius equation for further kinetic modeling. The results show that the HACA transformation of the embedded five-membered ring to a six-membered ring is possible, albeit slow. The most viable reaction mechanism involves the R2 + C 2 H 2 reaction, where the acetylene molecules adds to a σ-radical in the six-membered ring adjacent to the five-membered ring via a low entrance barrier. The predominant product of R2 + C 2 H 2 is predicted to be 3 ethynyl 4H cyclopenta[def]phenanthrene Pr5 via immediate H elimination from the initial addition complex. Next, Pr5 undergoes H-assisted isomerization to 4aH-pentaleno[4,3,2,1-cdef]phenanthrene Pr4, and the latter adds an H atom eventually forming the 1-pyrenylmethyl radical Pr3: R2 + C 2 H 2 ⇌ 3 ethynyl 4H cyclopenta[def]phenanthrene (Pr5) + H ⇌ 4aH-pentaleno[4,3,2,1-cdef]phenanthrene (Pr4) + H Pr5 + H ⇌ Pr4 + H Pr4 + H → 1-pyrenylmethyl (Pr3) This HACA sequence may be competitive with the methyl radical addition to the R1 radical formed by H abstraction from the CH 2 group in the five-membered ring of cyclopenta[d,e,f]phenanthrene, which provides a pathway to pyrene following two H atom losses. Relative contributions of the two mechanisms of the five- to six-membered ring transformation would strongly depend on the branching ratios of the R1 and R2 radicals produced by the H abstractions and the available concentration of C 2 H 2 vs. CH 3 and hence differ in different flames.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Roell, Garrett W.↗
DOE OSTI2024

Photophysical properties of three-coordinate heteroleptic Cu( I ) β-diketiminate triarylphosphine complexes

A series of heteroleptic copper(I) β-diketiminate triarylphosphine complexes is reported, having the general formula Cu(R 1 NacNac R2 )(PPh X 3 ), where R 1 NacNac R2 is a substituted β-diketiminate and PPh X 3 is a triphenylphosphine derivative. A total of five different R 1 NacNac R2 ligands and three different triarylphosphines are used to assemble the nine complexes. Here, the syntheses, X-ray crystal structures, cyclic voltammograms, and UV–vis absorption spectra of all compounds are described. Whereas most of the compounds are weakly luminescent or only luminesce at 77 K, the four complexes with the more sterically encumbered β-diketiminate ligands, with methyl or isopropyl substituents at the 2- and 6-positions of the N-phenyl rings, exhibit weak room-temperature photoluminescence with peaks between 519 and 566 nm and long excited-state lifetimes in the range of 15–70 μs. The sterically encumbering substituents in this subset have subtle effects on the UV–vis absorption maximum, which red shifts slightly as the steric bulk increases, as well as significant effects on the photoluminescence lifetime, which is observed to increase as the steric bulk is augmented. Substituents on the triarylphosphine also influence the excited-state dynamics in the bulky complexes, with the more electron-rich tris(4-methoxyphenyl)phosphine (PPh OMe 3 ) giving longer-excited-state lifetimes compared to triphenylphosphine (PPh 3 ) when the same R 1 NacNac R2 ligand is used.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗
DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗
DOE OSTI2020

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events

Abstract. High-time-resolution measurements of in situ aerosol and cloud properties provide the ability to study regional atmospheric processes that occur on timescales of minutes to hours. However, one limitation to this approach is that continuous measurements often include periods when the data collected are not representative of the regional aerosol. Even at remote locations, submicron aerosols are pervasive in the ambient atmosphere with many sources. Therefore, periods dominated by local aerosol should be identified before conducting subsequent analyses to understand aerosol regional processes and aerosol–cloud interactions. Here, we present a novel method to validate the identification of regional baseline aerosol data by applying a mathematical algorithm to the data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the eastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical, optical, and chemical properties at time resolutions from seconds to minutes. A second temporary supplementary facility (S1), located ∼0.75 km from C1, was deployed for ∼1 year during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate periods of high submicron number concentration (Ntot) in the fine-mode condensation particle counter (CPC) and size distributions from the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind direction using a meteorology sensor with local sources. Elevated concentrations of Aitken-mode (< 100 nm diameter) particles were observed in correspondence with the wind directions associated with airport operations. At ENA, the Graciosa Airport and its associated activities were found to be the main sources of high-concentration aerosol events at ENA, causing peaks in 1 min Ntot that exceeded 8000 and 10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with these wind directions were also observed. As a result, the diverse local sources at ENA yielded a poor relationship between Ntot measurements collected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when the wind direction was associated with the airport operations (west to northwest and southeast to south at C1 and east to south at S1) were applied. The meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1, and they did not significantly improve the relationship between the two sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and S1. After its parameterization and application, ENA-AM generated a high correlation between Ntot in the summer at C1 and S1 (R2=0.87 with a slope =0.84±0.001). We identified the regional baseline at ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer to understand submicron aerosol vertical mixing over C1. The high correlation (R2=0.71 with a slope of 1.04±0.01) observed between C1 and the AAF Ntot collected within an area of 10 km surrounding ENA and at altitudes < 500 m indicated that the submicron aerosol at ENA was well mixed within the first 500 m of the marine boundary layer during the month of July during ACE-ENA. Our novel method for determining a regional aerosol baseline at ENA can be applied to other time periods and at other locations with validation by a secondary site or additional collocated measurements.

54 ENVIRONMENTAL SCIENCES↗