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At least 73 records · Page 4

Aerosol characteristics at the Southern Great Plains site during the HI-SCALE campaign

Abstract. Large uncertainties exist in global climate model predictions of radiative forcing due to insufficient understanding and simplified numerical representation of cloud formation and cloud–aerosol interactions. The Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in north-central Oklahoma to provide a better understanding of land–atmosphere interactions, aerosol and cloud properties, and the influence of aerosol and land–atmosphere interactions on cloud formation. The HI-SCALE campaign consisted of two intensive observational periods (IOPs) (April–May and August–September, 2016), during which coincident measurements were conducted both on the G-1 aircraft platform and at the SGP ground site. In this study we focus on the observations at the SGP ground site. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Ionicon proton-transfer-reaction mass spectrometer (PTR-MS) were deployed, characterizing chemistry of non-refractory aerosol and trace gases, respectively. Contributions from various aerosol sources, including biogenic and biomass burning emissions, were retrieved using factor analysis of the AMS data. In general, the organic aerosols at the SGP site was highly oxidized, with oxygenated organic aerosol (OOA) identified as the dominant factor for both the spring and summer IOP though more aged in spring. Cases of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) and biomass burning events were further investigated to understand additional sources of organic aerosol. Unlike other regions largely impacted by IEPOX chemistry, the IEPOX SOA at SGP was more highly oxygenated, likely due to the relatively weak local emissions of isoprene. Biogenic emissions appear to largely control the formation of organic aerosol (OA) during the HI-SCALE campaign. Potential HOM (highly oxygenated molecule) chemistry likely contributes to the highly oxygenated feature of aerosols at the SGP site, with impacts on new particle formation and global climate.

54 ENVIRONMENTAL SCIENCES↗

Appalachian Basin Play Fairway Analysis Thermal Risk Factor and Quality Analyses

*This submission revises the analysis and products for Thermal Quality Analysis for the northern half of the Appalachian Basin (https://gdr.openei.org/submissions/638)* This submission is one of five major parts of a Low Temperature Geothermal Play Fairway Analysis. Phase 1 of the project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This submission includes a subset of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the project. This subset is those contents that were improved upon during calendar year 2016. Figures are provided as examples of some shapefiles and rasters. See also: Final Report: Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (https://gdr.openei.org/submissions/899). The 2015 data submission should be visited to obtain: 1) the regional standardized 1 square km grid used in the project as points (cell centers), polygons, and as a raster, 2) the raw well data for the state well temperature databases, 3) the COSUNA section shapefile and formation thermal conductivities by state as *.xlsx files, 4) the sediment thickness map and 30 m Digital Elevation Model for the Appalachian Basin as GeoTIFF raster files, 5) the BHT correction sections shapefile and drilling fluid databases as *.csv files, 6) the unbuffered interpolation regions as shapefiles, 7) several 50 km buffered interpolation regions as shapefiles, 8) several gridded interpolation regions as raster files, 9) an R script for organizing the thermal data and running the local spatial outlier analysis, 10) shapefiles and rasters for the prediction, uncertainty, and cross validation of the temperature at 1.5 km, 2.5 km, and 3.5 km depth, 11) shapefiles and rasters for the prediction, uncertainty, and cross validation depth to 100 degrees C, 12) an ArcGIS toolbox for thermal risk factor models, 13) an ArcGIS model for extracting results specific to each county of interest, 14) thermal resource cross section plots, 15) the geothermal Play Fairways.

15 GEOTHERMAL ENERGY↗

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗

Analysis of the Factors Contributing to Vertebral Compression Fractures After Spine Stereotactic Radiosurgery

Purpose: To determine our institutional vertebral compression fracture (VCF) rate after spine stereotactic radiosurgery (SRS) and determine contributory factors. Methods and Materials: Retrospective analysis from 2001 to 2013 at a single institution was performed. With institutional review board approval, electronic medical records of 1905 vertebral bodies from 791 patients who were treated with SRS for the management of primary or metastatic spinal lesions were reviewed. A total of 448 patients (1070 vertebral bodies) with adequate follow-up imaging studies available were analyzed. Doses ranging from 10 Gy in 1 fraction to 60 Gy in 5 fractions were delivered. Computed tomography and magnetic resonance imaging were used to evaluate the primary endpoints of this study: development of a new VCF, progression of an existing VCF, and requirement of stabilization surgery after SRS. Results: A total of 127 VCFs (11.9%; 95% confidence interval [CI] 9.5%-14.2%) in 97 patients were potentially SRS induced: 46 (36%) were de novo, 44 (35%) VCFs progressed, and 37 (29%) required stabilization surgery after SRS. Our rate for radiologic VCF development/progression (excluding patients who underwent surgery) was 8.4%. Upon further exclusion of patients with hematologic malignancies the VCF rate was 7.6%. In the univariate analyses, females (hazard ratio [HR] 1.54, 95% CI 1.01-2.33, P=.04), prior VCF (HR 1.99, 95% CI 1.30-3.06, P=.001), primary hematologic malignancies (HR 2.68, 95% CI 1.68-4.28, P<.001), thoracic spine lesions (HR 1.46, 95% CI 1.02-2.10, P=.02), and lytic lesions had a significantly increased risk for VCF after SRS. On multivariate analyses, prior VCF and lesion type remained contributory. Conclusions: Single-fraction SRS doses of 16 to 18 Gy to the spine seem to be associated with a low rate of VCFs. To the best of our knowledge, this is the largest reported experience analyzing SRS-induced VCFs, with one of the lowest event rates reported.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Trends and drivers of marine fish landings in Portugal since its entrance in the European Union

Abstract Marine landings in Portugal have decreased at a higher rate than fishing effort in the last 20 years. Identifying the variables driving the quantity and composition of landings is pivotal to understand the dynamics of the fisheries sector, which entails complex social and environmental aspects. In this study, we investigate the main drivers of marine fish landings in continental Portugal between 1989 and 2014. To identify common trends in time series, and quantify the importance of environmental factors, we applied a dynamic factor analysis considering four regions and three types of gear (trawling, purse-seine, and a multi-gear fishery). Our results show the importance of fishing effort as the most relevant factor driving marine landings in Portugal, both at the long and short terms. In addition, the effect of environmental factors such as the winter river discharge and the spring East Atlantic Teleconnection index should not be neglected, probably through mechanisms affecting coastal productivity. We provide a comprehensive amount of information that permits to improve our understanding of the trends of the most important commercial species in Portugal during the period of study.

Bueno-Pardo, Juan↗

An Analysis of Terrestrial and Aquatic Environmental Controls of Riverine Dissolved Organic Carbon in the Conterminous United States

Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general, high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.

54 ENVIRONMENTAL SCIENCES↗

Numerical Validation of an Algorithm for Combined Soiling and Degradation Analysis of Photovoltaic Systems

We describe and demonstrate an open-source algorithm for simultaneously quantifying degradation and soiling of photovoltaic (PV) systems from energy-production time series data. The new analysis is based on year-on-year degradation rate analysis combined with stochastic rate and recovery soiling analysis. The algorithm is designed to fit into the workflow provided by RdTools, a Python module maintained by NREL and collaboratively developed with the community, which provides a framework and functions for degradation and loss-factor analysis of PV field data. We demonstrate the method on numerically simulated PV data sets and show that it reduces the root-mean-square error of the P50 degradation rate estimate when soiling is present.

14 SOLAR ENERGY↗

Manuscript Workflows from and Processed Organic Matter Composition of Experimentally Burned Open Air and Muffle Furnace Vegetation Chars across Differing Burn Severity and Feedstock Types from Pacific Northwest, USA (v3)

This dataset includes processed organic matter chemistry data from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and vegetation materials representative of major land cover types of the Pacific Northwest, USA. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. Source data and associated metadata (including methods and geospatial information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022). This dataset provides processing scripts and processed data for both solid and dissolved phase organic matter characterization data from experimentally generated chars. These processed data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. The processed data were subsequently analyzed; and the results and ecological implications of the findings were published in peer-reviewed manuscripts. The scripts and workflows used to develop the manuscripts are also included in this data package.This data package was originally published June 2024. It was updated September 2024 (new and modified files) and in January 2025 (modified files). See the change history section in the readme for more details.This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), and folders containing (A) processed data; (B) general processing scripts; and (C) additional folders with specific manuscript analysis scripts and processed data. Step-by-step instructions to assist the user in recreating the workflow used to generate the results in the manuscripts is also provided. The processed data folder includes (1) a folder of processed Parallel Factor Analysis (PARAFAC) and spectra indices outputs from excitation emissions matrix (EEM) fluorescence and absorbance data; (2) a folder of processed solid state carbon-13 (13-C NMR) integrals; (3) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) processed data outputs from Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude), blank corrections and data aggregation, and calculated molecular indices. All files are .pdf, .csv, .html, .Rmd, .R, or .RData.

54 ENVIRONMENTAL SCIENCES↗

Effect of initial orientation on dynamic recrystallization of a zirconium alloy during hot deformation

Highlights: • The dynamic recrystallization process is enhanced by the operation of slip. • Continuous dynamic recrystallization is promoted by the rotation of grains. • Texture induced hardening hides the softening induced by dynamic recrystallization. - Abstract: The present study investigated the influence of the initial orientation on the dynamic recrystallization (DRX) behavior of a Zr-1Sn-0.3Nb alloy. A hot-rolled and annealed Zr sheet was compressed along two directions: along the normal direction so that the grains' -axis was nearly parallel to the loading direction (0° sample) and along the transverse direction so that the grains' -axis was nearly perpendicular to the loading direction (90° sample). The samples were compressed at 700 °C at a strain rate of 1 s{sup −1}. The microstructures at different strains were characterized by the electron backscatter diffraction (EBSD) technique, and conventional dislocation analysis using transmission electron microscope (TEM) was performed. A threshold value of grain orientation spread (GOS) equaled to 5° was used to distinguish the dynamically recrystallized grains from the deformed matrix. The results revealed that the DRX behavior strongly depended on the initial orientation. The Schmid factor analysis and TEM observation confirmed that pyramidal slip operated from the first stage of deformation in the 0° sample but not in the 90° sample. For the 0° sample, in the early and medium stages of deformation, due to the high stored energy caused by the operation of pyramidal slip, DDRX was mainly contributed to the formation of new fine grains. However, in the later stage of deformation, the DRX mechanism changed from DDRX to CDRX. In the 90° sample, although DDRX featured by grain boundary bulging occurred, the main DRX mechanism was CDRX in the whole deformation processing. Moreover, texture induced hardening in the early stage of deformation hides the softening induced by DDRX.

36 MATERIALS SCIENCE↗

Lung Shunt Fraction prior to Yttrium-90 Radioembolization Predicts Survival in Patients with Neuroendocrine Liver Metastases: Single-Center Prospective Analysis

ObjectiveTo investigate survival outcomes following radioembolization with Yttrium-90 (Y90) for neuroendocrine tumor liver metastases (NETLMs). This study was designed to assess the efficacy of Y90 radioembolization and to evaluate lung shunt fraction (LSF) as a predictor for survival.MethodsA single-center, prospective study of 44 consecutive patients (median age: 58.5 years, 29.5 % male) diagnosed with pancreatic (52.3 %) or carcinoid (47.7 %) NETLMs from 2006 to 2012 who underwent Y90 radioembolization was performed. Patients’ baseline characteristics, including LSF and median overall survival (OS) from first Y90 radioembolization, were recorded and compared between patients with high (≥10 %) and low (<10 %) LSF. Baseline comparisons were performed using Fisher’s exact tests for categorical and Mann–Whitney U test for continuous variables. Survival was calculated using the Kaplan–Meier method. Univariate (Wilcoxon rank-sum test) and multivariate analyses (Cox Proportional Hazard Model) for risk factor analysis were performed.ResultsThere was no statistically significant difference in age, gender, race, tumor properties, or previous treatments between patients with high (n = 15) and low (n = 29) LSF. The median OS was 27.4 months (95 %CI 12.73–55.23), with 4.77 months (95 %CI 2.87–26.73) for high and 42.77 months (95 %CI 18.47–59.73) for low LSF (p = 0.003). Multivariate analysis identified high LSF (p = 0.001), total serum bilirubin >1.2 mg (p = 0.016), and lack of pretreatment with octreotide (p = 0.01) as independent prognostic factors for poorer survival. Tumor type and total radiation dose did not predict survival.ConclusionsLSF ≥10 %, elevated bilirubin levels, and lack of pretreatment with octreotide were found to be independent prognostic factors for poorer survival in patients with NETLMs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Modeling and control of cascaded bridgeless multilevel rectifier under unbalanced load conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality. The complete design process of the proposed converter is developed step by step in order to meet all the desired objectives. The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to mathematically derive requirements for the number of partially controlled and fully controlled H-bridges in the proposed H-bridge converter. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. After exploring various well-established control methods, a novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization, power factor correction, and elimination of zero crossing current distortion under both balanced and unbalanced load conditions. The converter can also be used for reactive power compensation in a grid tied power system if a sufficient number of fully controlled H-bridge modules are included. Processor-In-the-Loop (PIL) simulation has been the utilized to validate the performance of discrete control structure. Simulation and experimental results validate the models and control method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effect of nanoparticles size and polyelectrolyte on nanoparticles aggregation in a cellulose fibrous matrix

Controlling nanoparticles (NPs) aggregation in cellulose/NPs composites allows to optimise NPs driven properties and their applications. Polyelectrolytes are used to control NPs aggregation and their retention within the fibrous matrix. Here in this study, we aim at evaluating how a polyelectrolyte (Cationic Polyacrylamide; CPAM, molecular weight: 13 MDa, charge: 50%, Radius of gyration: 30–36 nm) adsorbs and re-conforms onto the surface of silica(SiO 2 ) NPs differing in diameter (8, 22 and 74 nm) and to investigate the respective NPs aggregation in cellulose matrices. SEM shows the local area distribution of NPs in composites. Ultra-SAXS (USAXS) allows to evaluate the average NPs size distribution and the inter-particle interactions at length scale ranging from 1 to 1000 nm. USAXS data analysis reveals that CPAM covers multiple NPs of the smaller diameter (8 nm), presumably with a single chain to form large size NPs aggregates. As the NPs diameter is increased to 22 nm, CPAM re-conforms over NP surface forming a large shell of thickness 5.5 nm. For the composites with NPs of diameter 74 nm, the CPAM chain re-conforms further onto NP surface and the surrounding shell thickness decreases to 2.2 nm. Lastly, structure factor analysis reveals higher structural ordering for NPs as increases their diameter, which is caused by different conformations adopted by CPAM onto NPs surface.

36 MATERIALS SCIENCE↗

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗

Implications of a Pervasive Climate Model Bias for Low‐Cloud Feedback

Abstract How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

58 GEOSCIENCES↗

Dissolved organic matter transport reflects hillslope to stream connectivity during snowmelt in a montane catchment

Dissolved organic matter (DOM) transport is a key biogeochemical linkage across the terrestrial-aquatic interface in headwater catchments, and quantifying the biological and hydrological controls on DOM composition provides insight into DOM cycling at the catchment scale. In this paper, we evaluated the mobility of DOM components during snowmelt in a montane, semiarid catchment. DOM composition was evaluated on a near-daily basis within the soil and the stream during snowmelt, and was compared to groundwater samples using a site-specific parallel factor analysis (PARAFAC) model derived from soil extracts. The fluorescent component loadings in the interstitial soil water and in the groundwater were significantly different and did not temporally change during snowmelt. In the stream, a transition occurred during snowmelt from fluorescent DOM with higher contributions of amino acid-like components indicative of groundwater to higher humic-like contributions indicative of soil water. Furthermore, we identified a humic-like fluorescent component in the soil water and the stream that is typically only observed in extracted water soluble organic matter from soil which may suggest hillslope to stream connectivity over very short time scales. Qualitative interpretations of changes in stream fluorescent DOM were supported by two end-member mixing analyses of conservative tracers. After normalizing fluorescent DOM loadings for dissolved organic carbon (DOC) concentration, we found that the peak in DOC concentration in the stream was driven by the nonfluorescent fraction of DOM. Finally, this study demonstrated how PARAFAC analysis can be used to refine our conceptual models of runoff generation sources, as well as provide a more detailed understanding of stream chemistry dynamics.

58 GEOSCIENCES↗

Vertical Stratification of Peat Pore Water Dissolved Organic Matter Composition in a Peat Bog in Northern Minnesota: Pore Water DOM composition in a peat bog

We characterized dissolved organic matter (DOM) composition throughout the peat column at the Marcell S1 forested bog in northern Minnesota and tested the hypothesis that redox oscillations associated with cycles of wetting and drying at the surface of the fluctuating water table correlate with increased carbon, sulfur and nitrogen turn over. We found significant vertical stratification of DOM molecular composition and EEM-PARAFAC components within the peat column. In particular the intermediate depth zone (~ 50 cm) was identified as a zone where maximum decomposition and turnover is taking place. Surface DOM was dominated by inputs from surface vegetation. The intermediate-depth zone was an area of high organic matter reactivity and increased microbial activity with diagenetic formation of many unique compounds, among them polycyclic aromatic compounds (PAC) that contain both nitrogen and sulfur heteroatoms. These compounds have been previously observed in coal-derived compounds and were assumed to be responsible for coal's biological activity. Biological processes triggered by redox oscillations taking place at the intermediate depth zone of the peat profile at the S1 bog are assumed to be responsible for the formation of these heteroatomic PACs in this system. Alternatively these compounds could stem from black carbon and nitrogen derived from fires that have occurred at the site in the past. Surface and deep DOM exhibited more similar characteristics, compared to the intermediate-depth zone, with the deep layer exhibiting greater input of microbially degraded organic matter than the surface suggesting that the entire peat profile consists of similar parent material at different degrees of decomposition and that lateral and vertical advection of pore water from the surface to the deeper horizons is responsible for such similarities. Our findings suggest that molecular composition of DOM in peatland pore water is dynamic and is a function of ecosystem activity, water table and redox oscillation and porewater advection.

Environmental Molecular Sciences Laboratory↗

Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high‐resolution mass spectrometry data across a freshwater stream network

Abstract Advancing our understanding of dissolved organic matter (DOM) chemistry in aquatic systems necessitates the integration of data streams from multiple analytical platforms. Some measurements require pretreatment with solid phase extraction (SPE), while others are performed directly on whole water samples. Evidence has suggested that SPE will be biased against select DOM fractions, leading to concerns over the ability to establish data linkages across platforms with variable needs for SPE pretreatment, such as those from optical measurements and those that provide high‐resolution molecular information. Here, we directly addressed this concern by assessing the impact of SPE on DOM optical properties through excitation–emission matrices with parallel factor analysis (PARAFAC) for 47 samples across a stream network within a single watershed reflective of variable DOM sources. PARAFAC data was further paired with molecular information obtained by Fourier transform ion cyclotron resonance mass spectrometry (FTICR‐MS). A comparison of PARAFAC models first revealed no systematic qualitative differences in major components between whole water DOM and DOM isolated by SPE (SPE‐DOM); however, quantitative biases against select components were observed. Further linkages with FTICR‐MS data revealed that the molecular fingerprint associated with each PARAFAC component was consistent between the whole water DOM and SPE‐DOM. Our results suggest that bulk scale linkages across these analytical platforms could be inferred irrespective of the observed quantitative biases resulting from SPE for samples within this example watershed. This work represents a key step toward the systematic evaluation of linkages between optical and high‐resolution mass spectrometry datasets in freshwater lotic environments.

59 BASIC BIOLOGICAL SCIENCES↗