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At least 217 records · Page 12

Dissection of Carbon and Nitrogen Cycling in Post-Fire Soil Environments using a Genome- Informed Experimental Community (Final Technical Report)

Wildfires are a natural part of many forest ecosystems, with globally important carbon (C) storage and nutrient cycling consequences, and they are increasing in frequency and severity in Western North America. Forest fires affect soil C stocks in complex ways; some C is released into the atmosphere through combustion, while a large percentage of the C is added to the soil in the form of pyrogenic organic matter. Worldwide, it is estimated that 16% of soil organic matter is pyrogenic, while locally, this number may be as high as 80%. Understanding how wildfires affect soil organic matter cycling requires understanding how microbes respond to pyrogenic organic matter and other post-fire soil conditions. However, our understanding of microbial interactions within post-fire soil was in its infancy at the time of our proposal. Outstanding questions included: Which microbes are capable of degrading pyrogenic organic matter? What are the relevant genes and metabolites associated with this degradation? What are the key interactions among post-fire microbes? Key highlights of outcomes supported by this grant included training eleven early-career scientists and two early-career PIs, publication of twelve peer-reviewed papers, cross-lab collaborations that empowered complex scientific approaches, the development of an open-source automated gas sampler to drive novel insights in C cycling, enhanced understanding of post-fire microbial community dynamics, and novel genetic and molecular insights into microbial responses to fire.

54 ENVIRONMENTAL SCIENCES↗

Investigating spatial variability of aerosol, cloud condensation nuclei, and ice nucleating particles in mountainous terrain

The ASR-supported Surface Atmosphere Integrated field Laboratory (SAIL) in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the East River Watershed as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the ARM Mobile Facility (AMF-2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small particle counter (POPS, (Gao et al., 2016)), CNN using a miniature CCN counter (CloudPuck), and INP using the Time-Resolved Aerosol Filter Sampler (TRAPS, Creamean et al. (2018)). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al., 2019; Kelly et al., 2021; Asher et al., 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al., 2017; Popoola et al., 2018; Caubel et al., 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al., 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al., 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies.

54 ENVIRONMENTAL SCIENCES↗

Measuring the Aerosol Collection Efficiency and Detector Face Deposition of the Bladewerx KatanaGBM™ (Glove Box Monitor) Continuous Air Monitor

To assist Bladewerx LLC (the Requestor) in testing their new CAM (continuous air monitor) sampler model Bladewerx™ KatanaGBM™ (Glove Box Monitor), the Laboratory (LANL, i.e. Los Alamos National Laboratory) measured the aerosol particle collection efficiency and detector face deposition for several experimental test conditions. Bladewerx LLC provided a prototype KatanaGBM with a set of requested tests. According to these parameters, LANL designed and performed a series of experiments to (A.) Measure the aerosol particle collection efficiency and detector face deposition of the KatanaGBM at three air flow rates of 5, 42, and 70 ALPM (ambient liters per minute), (B.) Measure the collection efficiency and detector face deposition using two sizes of oil droplet particles: 3±1 and 10±1 µm (micron) AED (aerodynamic equivalent diameter), and (C.) Test the KatanaGBM for aerosol collection efficiency and detector face deposition with the wind tunnel’s air flow at three different angles 0°, 45° and 90° (compared to the KatanaGBM’s filter face).

61 RADIATION PROTECTION AND DOSIMETRY↗

Investigating Spatial Variability of Aerosol, Cloud Condensation Nuclei, and Ice Nucleating Particles in Mountainous Terrain Field Campaign Report

The U.S. Department of Energy Atmospheric System Research (ASR)-supported Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the ERW as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the second ARM Mobile Facility (AMF2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small portable optical particle spectrometer (POPS; Gao et al. 2016), cloud condensation nuclei (CNN) using a miniature CCN counter (CloudPuck), and ice nucleating particles (INP) using the time-resolved aerosol filter sampler (TRAPS; Creamean et al. 2018). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al. 2019, Kelly et al. 2021, Asher et al. 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al. 2017, Popoola et al. 2018, Caubel et al. 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al. 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al. 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in the ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies. We met this goal by answering the following science questions: 1. What is the aerosol temporal variability, and how does aerosol inhomogeneity vary seasonally? Is there significant seasonal variability in sources, or are short-term meteorological conditions the most important determining factor in sources for cloud nuclei? 2. What is the aerosol spatial variability? What are the aerosol characteristics at cloud base, presumably the particles most representative of those acting as cloud nuclei? 3. How should measurement networks be designed to capture aerosol-cloud interactions, and what do they need to measure? Can a single measurement site accurately represent aerosol properties in regions of complex terrain? SAIL-Net consisted of six measurement nodes spread across the ERW near Crested Butte, Colorado. The primary objective in site placement was to select locations that captured the vertical variation in aerosol properties while also spanning the domain of the SAIL campaign. The elevation of the sites ranged from roughly 2750 m along the valley floor of the ERW to approximately 3500 m near the top of Crested Butte Mountain, which is one of the taller peaks in the ERW. The farthest distance between sites was 14 km, while the closest two sites were approximately 1 km apart. Two of the sites were collocated with the ARM SAIL sites; our instruments sat on top of one of the trailers at AOS and another one of our sites was located in a meadow just above AMF2.

54 ENVIRONMENTAL SCIENCES↗

In-Field Alpha Spectrometer Development FY2022 Mid-Year Report

In response to needs identified by the International Atomic Energy Agency (IAEA), Idaho National Laboratory (INL) has developed an In-Field Alpha Spectrometer (IFAS) to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF 6 ) at processing facilities, to perform field assessments to verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, developed at Pacific Northwest National Laboratory (PNNL), which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (as a dihydrate, UO 2 F 2 ·2H 2 O). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the course of this project INL, PNNL, Oak Ridge National Laboratory worked to optimize the SUDA sample design for alpha spectrometry, to optimize processes for manufacturing, loading, and shipping SUDA samples, and to allow the measurement of loaded SUDA samples. In fiscal year (FY) 2022 INL has bene investigating the reproducibility and measurement precision of IFAS measurements and the associated determination of uranium enrichment.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Particulate Effluent Characterization (Final Report)

Understanding particulate emissions from nuclear facilities could help differentiate between normal nuclear operations and potential nuclear accidents or nuclear weapons tests. Oak Ridge National Laboratory (ORNL) is unique in that there are several types of nuclear facilities on site: an operating production reactor, radiochemical separation facilities, and a spallation neutron source. This project deployed a high-volume particulate air filter sampler to collect airborne particulate effluent from the nuclear facilities on site at ORNL. Collections occurred regularly from November 1, 2024, through June 30, 2025, and were analyzed via gamma spectroscopy in the laboratory. The radioisotope iodine-123 ( 123 I) was detected in several samples throughout the collection period. Detailed atmospheric transport modeling was performed on all detections for source attribution, and the most likely source of the 123 I was determined to be the Spallation Neutron Source. The project demonstrated the viability of ORNL as a test bed for effluent monitoring studies.

54 ENVIRONMENTAL SCIENCES↗

KBase Narrative - Atacama Trench & Sn Clemente 2018 cruise Metagenomes -Decontamination through Metagenomic Fractionation and analysis of Metabolic Potential-

Deep-sea microbiomes sampled with traditional or pressure-retaining instrumentation A fundamental property of life in the sea is that with increasing depth must come increased adaptation to elevated hydrostatic pressures. This project aims to assess technology for the accurate characterization of microbial biodiversity and biochemistry at greater depths, and validate its use in some of the deepest and least-explored waters in the Ocean: Hadal Trench. Compared to the 0.1 megapascal (MPa) of surface waters, organisms inhabiting at the average depth of the Ocean (3800 m) have to deal with pressures of 38 MPa (5,500 psi). The effects of these high pressure have been most thoroughly investigated in microorganisms, where it has been found to affect membrane integrity and transport, cytoskeletal assembly and both DNA and protein synthesis. We will explore the diversity and activity of microorganisms from 2000 m to >8,000 m depths within the highly productive water column of hadal trenches, comparing seawater samples obtained with and without substantial pressure changes during recovery. A pressure retaining device was used to sample the microbial communities of the watercolumn with reduced decompression during retreival (Peoples et. al., 2019). References: Peoples LM, Norenberg M, Price D, McGoldrick M, Novotny M, Bochdansky A, Bartlett DH. A full-ocean-depth rated modular lander and pressure-retaining sampler capable of collecting hadal-endemic microbes under in situ conditions. Deep Sea Research Part I: Oceanographic Research Papers. 2019 Jan 1;143:50-7.

Plominsky, Alvaro M.↗

KBase Narrative - Atacama Trench & Sn Clemente 2018 cruise Metagenomes -Sequence quality filtration & Assembly-

Deep-sea microbiomes sampled with traditional or pressure-retaining instrumentation A fundamental property of life in the sea is that with increasing depth must come increased adaptation to elevated hydrostatic pressures. This project aims to assess technology for the accurate characterization of microbial biodiversity and biochemistry at greater depths, and validate its use in some of the deepest and least-explored waters in the Ocean: Hadal Trench. Compared to the 0.1 megapascal (MPa) of surface waters, organisms inhabiting at the average depth of the Ocean (3800 m) have to deal with pressures of 38 MPa (5,500 psi). The effects of these high pressure have been most thoroughly investigated in microorganisms, where it has been found to affect membrane integrity and transport, cytoskeletal assembly and both DNA and protein synthesis. We will explore the diversity and activity of microorganisms from 2000 m to >8,000 m depths within the highly productive water column of hadal trenches, comparing seawater samples obtained with and without substantial pressure changes during recovery. A pressure retaining device was used to sample the microbial communities of the watercolumn with reduced decompression during retreival (Peoples et. al., 2019). References: Peoples LM, Norenberg M, Price D, McGoldrick M, Novotny M, Bochdansky A, Bartlett DH. A full-ocean-depth rated modular lander and pressure-retaining sampler capable of collecting hadal-endemic microbes under in situ conditions. Deep Sea Research Part I: Oceanographic Research Papers. 2019 Jan 1;143:50-7.

Plominsky, Alvaro M.↗

Cellulose molecular weight of corn stover with cotreatment

Here we present a dataset of cellulose molecular weights from corn stover after a cotreatment process. The corn stover sample was subjected to a combination of mechanical disruption (ball milling) and consolidated bioprocessing (CBP) process using the bacterium C. thermocellum at 60 grams/L solids loadings. Cellulose was isolated from control, no cotreatment control, and cotreatment corn stover. Cellulose was then derivatized using anhydrous pyridine and phenyl isocyanate over 48 h at 70 ºC. The reaction was quenched by anhydrous methanol. Methanol and water mixture (7:3, v/v) was added dropwise to promote precipitation of the cellulose derivative. The solids were collected by filtration and thoroughly washed with the methanol and water mixture followed by water. The cellulose derivative was dried overnight under vacuum at 40°C. The obtained cellulose tricarbanilates was then dissolved in tetrahydrofuran (THF) at 1.0 mg/mL and the solution was filtered through a 0.45 µm PTFE filter and placed in an auto-sampler vial. The molecular weight of cellulose was measured by Agilent GPC SECurity 1200 system equipped with four Waters Styragel columns (i.e., HR0.5, HR2, HR4, and HR6) and a UV detector (270 nm). THF was used as the mobile phase. Data collection and processing was performed by Polymer Standards Service WinGPC Unity software (Build 6807). The molecular weight was calculated relative to the polystyrene calibration curve. The data on molecular weights provided information about the effects of cotreatment on corn stover cellulose molecular changes.

Cellulose, molecular weights, corn stover, cotreat↗

Editorial: Deep-sea observation equipment and exploration technology

The increasing interest in deep-sea exploration is a crucial catalyst for driving advancements in deep-sea observation technology research. Numerous sophisticated sensors have been developed to facilitate comprehensive studies in deep-sea physics, chemistry, and geology. For example, cutting-edge small and compact seabed samplers are now employed on various platforms, such as Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), and Human-Operated Vehicles (HOVs), enabling observation of the hadal zone. Additionally, Micro-electromechanical systems (MEMS) sensors are routinely utilized for ocean wave observation. This Research Topic aims to foster new insights into ocean exploration and observation technology, including ocean sensor technology, ocean observation platforms, and ocean observation reliability technology.

47 OTHER INSTRUMENTATION↗

SARS-CoV-2 raw wastewater surveillance from student residences on an urban university campus

The COVID-19 pandemic brought about an urgent need to monitor the community prevalence of infection and detect the presence of SARS-CoV-2. Testing individual people is the most reliable method to measure the spread of the virus in any given community, but it is also the most expensive and time-consuming. Wastewater-based epidemiology (WBE) has been used since the 1960s when scientists implemented monitoring to measure the effectiveness of the Polio vaccine. Since then, WBE has been used to monitor populations for various pathogens, drugs, and pollutants. In August 2020, the University of Tennessee-Knoxville implemented a SARS-CoV-2 surveillance program that began with raw wastewater surveillance of the student residence buildings on campus, the results of which were shared with another lab group on campus that oversaw the pooled saliva testing of students. Sample collection began at 8 am, and the final RT-qPCR results were obtained by midnight. The previous day’s results were presented to the campus administrators and the Student Health Center at 8 am the following morning. The buildings surveyed included all campus dormitories, fraternities, and sororities, 46 buildings in all representing an on-campus community of over 8,000 students. The WBE surveillance relied upon early morning “grab” samples and 24-h composite sampling. Because we only had three Hach AS950 Portable Peristaltic Sampler units, we reserved 24-h composite sampling for the dormitories with the highest population of students. Samples were pasteurized, and heavy sediment was centrifuged and filtered out, followed by a virus concentration step before RNA extraction. Each sample was tested by RT-qPCR for the presence of SARS-CoV-2, using the CDC primers for N Capsid targets N1 and N3. The subsequent pooled saliva tests from sections of each building allowed lower costs and minimized the total number of individual verification tests that needed to be analyzed by the Student Health Center. Our WBE results matched the trend of the on-campus cases reported by the student health center. The highest concentration of genomic copies detected in one sample was 5.06 × 10 7 copies/L. Raw wastewater-based epidemiology is an efficient, economical, fast, and non-invasive method to monitor a large community for a single pathogen or multiple pathogen targets.

60 APPLIED LIFE SCIENCES↗

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

sampling timing↗

Performing Bayesian Analyses With AZURE2 Using BRICK: An Application to the 7 Be System

Phenomenological R-matrix has been a standard framework for the evaluation of resolved resonance cross section data in nuclear physics for many years. It is a powerful method for comparing different types of experimental nuclear data and combining the results of many different experimental measurements in order to gain a better estimation of the true underlying cross sections. Yet a practical challenge has always been the estimation of the uncertainty on both the cross sections at the energies of interest and the fit parameters, which can take the form of standard level parameters. Frequentist (χ 2 -based) estimation has been the norm. In this work, a Markov Chain Monte Carlo sampler, emcee, has been implemented for the R-matrix code AZURE2, creating the Bayesian R-matrix Inference Code Kit (BRICK). Bayesian uncertainty estimation has then been carried out for a simultaneous R-matrix fit of the 3 He (α,γ) 7 Be and 3 He (α,α) 3 He reactions in order to gain further insight into the fitting of capture and scattering data. Both data sets constrain the values of the bound state α-particle asymptotic normalization coefficients in 7 Be. The analysis highlights the need for low-energy scattering data with well-documented uncertainty information and shows how misleading results can be obtained in its absence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling PAH Mixture Interactions in a Human In Vitro Organotypic Respiratory Model

One of the most significant challenges in human health risk assessment is to evaluate hazards from exposure to environmental chemical mixtures. Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous contaminants typically found as mixtures in gaseous and particulate phases in ambient air pollution associated with petrochemicals from Superfund sites and the burning of fossil fuels. However, little is understood about how PAHs in mixtures contribute to toxicity in lung cells. To investigate mixture interactions and component additivity from environmentally relevant PAHs, two synthetic mixtures were created from PAHs identified in passive air samplers at a legacy creosote site impacted by wildfires. The primary human bronchial epithelial cells differentiated at the air–liquid interface were treated with PAH mixtures at environmentally relevant proportions and evaluated for the differential expression of transcriptional biomarkers related to xenobiotic metabolism, oxidative stress response, barrier integrity, and DNA damage response. Component additivity was evaluated across all endpoints using two independent action (IA) models with and without the scaling of components by toxic equivalence factors. Both IA models exhibited trends that were unlike the observed mixture response and generally underestimated the toxicity across dose suggesting the potential for non-additive interactions of components. Overall, this study provides an example of the usefulness of mixture toxicity assessment with the currently available methods while demonstrating the need for more complex yet interpretable mixture response evaluation methods for environmental samples.

3D in vitro models↗

Detecting and Characterizing Mg ii Absorption in DESI Survey Validation Quasar Spectra

Abstract We present findings of the detection of Magnesium II (Mg ii , λ = 2796, 2803 Å) absorbers from the early data release of the Dark Energy Spectroscopic Instrument (DESI). DESI is projected to obtain spectroscopy of approximately 3 million quasars (QSOs), of which over 99% are anticipated to be at redshifts greater than z > 0.3, such that DESI would be able to observe an associated or intervening Mg ii absorber illuminated by the background QSO. We have developed an autonomous supplementary spectral pipeline that detects these systems through an initial line-fitting process and then confirms the line properties using a Markov Chain Monte Carlo sampler. Based upon a visual inspection of the resulting systems, we estimate that this sample has a purity greater than 99%. We have also investigated the completeness of our sample in regard to both the signal-to-noise properties of the input spectra and the rest-frame equivalent width ( W 0 ) of the absorber systems. From a parent catalog containing 83,207 quasars, we detect a total of 23,921 Mg ii absorption systems following a series of quality cuts. Extrapolating from this occurrence rate of 28.8% implies a catalog at the completion of the five-year DESI survey that will contain over eight hundred thousand Mg ii absorbers. The cataloging of these systems will enable significant further research because they carry information regarding circumgalactic medium environments, the distribution of intervening galaxies, and the growth of metallicity across the redshift range 0.3 ≤ z < 2.5.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimizing Optical Searches for Supermassive Black Hole Binaries in Active Galactic Nuclei Light Curves: Fourier versus Bayesian Periodicity Detection

Simulations predict that supermassive black hole binaries (SMBHBs) will exhibit periodic brightness variations that may exceed the stochastic variability intrinsic to active galactic nuclei (AGN). In this paper, we simulate SMBHBs with damped random walk (DRW) AGN variability and an added sinusoidal signal from the orbital motion, and test three methods—a generalized Lomb–Scargle periodogram (GLSP), a nested Bayesian sampler (NBS), and a weighted wavelet z-transform (or WWZ)—to determine which is best at recovering the periodicity. Our simulated light curves follow the properties of the Catalina Real-Time Transient Survey (or CRTS), Legacy Survey of Space and Time (LSST), and Zwicky Transient Facility (ZTF) to best inform current and future SMBHB searches. We map a broad range of parameter space and identify which DRW-only light curves best mimic periodicity and pass each method’s model selection. The NBS performs best at detecting periodicity and filtering out DRW-only light curves. Combined candidate selection with both the NBS and GLSP significantly reduces false-positive rates (FPRs) with marginal impact on true-positive rates (TPRs). With this joint model selection pipeline, we find the lowest FPRs in ZTF-like simulations and the highest detection rates in LSST-like simulations. Using a modified computation of the false-alarm probability with GLSP, we efficiently triage LSST AGN light curves (∼10 7 light curves in ∼10–30 hr) and achieve TPRs and FPRs of ∼40% and ∼0.5%, respectively.

Banaszak, Sebastian M. [Vanderbilt Univ., Nashvill↗

Seasonal investigation of ultrafine-particle organic composition in an eastern Amazonian rainforest

Abstract. Reports on the composition of ultrafine particles (<100 nm in diameter) in the Amazon are scarce, due in part to the fact that new-particle formation has rarely been observed near ground level. Ultrafine particles near the surface have nevertheless been observed, leaving open questions regarding the sources and chemistry of their formation and growth, particularly as these vary across seasons. Here, we present measurements of the composition of ultrafine particles collected in the Tapajós National Forest (2.857° S, 54.959° W) during three different seasonal periods: 10–30 September 2016 (SEP), 18 November–23 December 2016 (DEC), and 22 May–21 June 2017 (JUN). Size-selected (5–70 nm) particles were collected daily (for 22 h each day) using an offline sampler. Samples collected during the three time periods were compiled and analyzed using liquid chromatography coupled with Orbitrap high-resolution mass spectrometry. Our findings suggest a sustained influence of isoprene organosulfate chemistry on ultrafine particles from the different periods. We present chemical evidence that indicates that biological-spore fragmentation impacted ultrafine-particle composition during the late wet season (JUN), while chemical markers for biomass burning and secondary chemistry peaked during the dry season (SEP and DEC). Higher oxidation states and degrees of unsaturation were observed for organics in the dry season (SEP and DEC), suggesting greater extents of aerosol aging. Finally, applying a volatility parameterization to the observed compounds suggests that organic sulfur species are likely key drivers of new-particle growth in the region due to their low volatility compared to other species.

54 ENVIRONMENTAL SCIENCES↗

Quantitative chemical assay of nanogram-level particulate matter using aerosol mass spectrometry: characterization of particles collected from uncrewed atmospheric measurement platforms

Abstract. Aerosol generation techniques have expanded the utility of aerosol mass spectrometry (AMS) for offline chemical analysis of airborne particles and droplets. However, standard aerosolization techniques require relatively large liquid volumes (e.g., several milliliters) and high sample masses that limit their utility. Here we report the development and characterization of a micronebulization AMS (MN-AMS) technique that requires as low as 10 µL of sample and can provide the quantification of the nanogram level of organic and inorganic substances via the usage of an isotopically labeled internal standard (34SO42-). Using standard solutions, the detection limits for this technique were determined at 0.19, 0.75, and 2.2 ng for sulfate, nitrate, and organics, respectively. The analytical recoveries for these species are 104 %, 87 %, and 94 %, respectively. This MN-AMS technique was applied successfully to analyze filter and impactor samples collected using miniature particulate matter (PM) samplers deployable on uncrewed atmospheric measurement platforms, such as uncrewed aerial systems (UASs) and tethered balloon systems (TBSs). Chemical composition of PM samples collected from a UAS field campaign conducted at the Department of Energy's (DOE) Southern Great Plains (SGP) observatory was characterized. The offline MN-AMS data compared well with the in situ PM composition measured by a co-located aerosol chemical speciation monitor (ACSM). In addition, the MN-AMS and ion chromatography (IC) agreed well for measurements of sulfate and nitrate concentrations in the PM extracts. This study demonstrates the utility of combining MN-AMS with uncrewed measurement platforms to provide quantitative measurements of ambient PM composition.

54 ENVIRONMENTAL SCIENCES↗