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DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Integrating environmental understanding into freshwater floatovoltaic deployment using an effects hierarchy and decision trees

Abstract In an era of looming land scarcity and environmental degradation, the development of low carbon energy systems without adverse impacts on land and land-based resources is a global challenge. ‘Floatovoltaic’ energy systems—comprising floating photovoltaic (PV) panels over water—are an appealing source of low carbon energy as they spare land for other uses and attain greater electricity outputs compared to land-based systems. However, to date little is understood of the impacts of floatovoltaics on the hosting water body. Anticipating changes to water body processes, properties and services owing to floatovoltaic deployment represents a critical knowledge gap that may result in poor societal choices and water body governance. Here, we developed a theoretically-derived hierarchical effects framework for the assessment of floatovoltaic impacts on freshwater water bodies, emphasising ecological interactions. We describe how the presence of floatovoltaic systems may dramatically alter the air-water interface, with subsequent implications for surface meteorology, air-water fluxes and physical, chemical and biological properties of the recipient water body. We apply knowledge from this framework to delineate three response typologies—‘ magnitude’ , those for which the direction and magnitude of effect can be predicted; ‘ direction’ , those for which only the direction of effect can be predicted; and ‘ uncertain’ , those for which the response cannot be predicted—characterised by the relative importance of levels in the effects hierarchy. Illustrative decision trees are developed for an example water body response within each typology, specifically, evaporative water loss, cyanobacterial biomass, and phosphorus release from bed sediments, and implications for ecosystem services, including climate regulation, are discussed. Finally, the potential to use the new understanding of likely ecosystem perturbations to direct floatovoltaic design innovations and identify future research priorities is outlined, showcasing how inter-sectoral collaboration and environmental science can inform and optimise this low carbon, land-sparing renewable energy for ecosystem gains.

Environmental Sciences & Ecology↗
DOE OSTI2020

Micro-Pulse DIAL for Atmospheric Water Vapor Profiling (Phase I Final Report)

Water vapor plays a key role in Earth’s climate and weather patterns. Accurate, high resolution measurements of the water vapor vertical profiles in a region have been found to significantly improve the numerical weather prediction models’ short-term forecasts, precipitation forecasts, as well as severe weather forecasts. However, current measurement techniques provide very coarse resolution in space, time, and/or altitude. A network of continuously sampling water vapor profilers would greatly expand the scientific knowledge of the atmosphere and serve as a valuable input into numerical weather models. This would be of interest not only to the Department of Energy’s Environmental Sciences Division but to other institutions such as the National Weather Service, the National Center for Atmospheric Research, the Federal Emergency Management Agency, and the military.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nuclear and Chemical Sciences Division: Investment Strategy 2023

The mission of the Nuclear and Chemical Sciences (NACS) Division within the Physical and Life Sciences (PLS) Directorate is to advance scientific understanding, capabilities, and technologies in nuclear and particle physics, radiochemistry, forensic science, and isotope systems to support LLNL’s national security mission. NACS Division personnel conduct a diverse range of research activities in particle physics, nuclear physics, radiation detection, nuclear measurements, chemical and nuclear forensic science, nuclear and radiochemistry, isotope geochemistry, and environmental science. These areas are leveraged to address evolving national security challenges. Scientific research provides the foundation for addressing these challenges, and it is also the principal means of attracting, training, and retaining staff scientists who can deliver solutions across the Laboratory’s mission space. The overarching strategy is to position the NACS Division at the nexus between fundamental nuclear and chemical science research and nuclear security applications. This approach will support efforts to recruit, train, and retain top-flight scientists and engineers who will play a key role in executing the Laboratory’s core nuclear security missions, while also enhancing LLNL’s reputation as a center for innovative scientific research. This document describes the strategic vision that will be used to guide key investments aimed at enabling NACS scientists to lead new efforts and meet future challenges.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Machine Learning in Environmental Chemistry: Application to Surface Complexation Modeling

Environmental chemistry – or biogeochemistry – is the scientific discipline typically invoked when examining and quantifying groundwater or surface water contamination, and nutrient cycling in the environment. Over the last three decades, there have been significant advances in mechanistic model development to describe and predict these complex biogeochemical processes. In particular, surface complexation models (SCMs) have been developed to describe the rock/soil surface reactions of metals and radionuclides, and their partitioning between various mobile species in the aqueous phase or immobile species sorbed on solid surfaces. Often represented by a simplified linear isotherm constant – Kd – in reactive transport models, these reactions play a critical role in many environmental science applications; particularly in contamination risk assessments and nuclear waste disposal performance assessments. In the past several decades, efforts by various institutions across the world have focused on developing SCMs based on datasets from laboratory measurements, including the identification of key parameters such as equilibrium constants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Artificial Intelligence for Earth System Predictability (AI4ESP) (2021 Workshop Report)

In October 2021, the U.S. Department of Energy (DOE) welcomed participants to the Artificial Intelligence for Earth System Predictability (AI4ESP) Workshop, hosted by the Office of Biological and Environmental Research (BER)—Advanced Scientific Computing Research (ASCR). The workshop is part of BER-ASCR’s ambition to more radically and aggressively advance prediction capabilities in the climate, Earth, and environmental sciences through the use of modern data analytics and artificial intelligence (AI). Advances in these capabilities are needed to improve predictions of climate change and extreme events that provide actionable information for planning and building resilience to their impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Water chemistry in flume channel and hyporheic zone (i.e., porewater) associated with: “Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry”

Dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), molecular data for organic matter, and biochemical reactions for surface water and porewater (i.e., hyporheic zone) collected from a water recirculating flume located at the University of Texas, Austin. The flume contained real river water from Lower Colorado River(Austin, TX) and clean sand. Hyporheic exchange in the flume was induced through The study aims to understand relationships between aerobic metabolism of organic matter and molecular characteristics of organic matter, such as thermodynamic signature and nitrogen content, through the extent of the hyporheic zone at 10 cm- resolution, and through time. During the experiment, organic matter (dry leaves) was added to the flume and removed after 24 hours. The water samples were collected before the addition of leaves, at the time of removal of leaves, and at hour 72. The water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and total organic carbon (TOC) and total nitrogen (TN) analysis. Dissolved oxygen content throughout the surface water and the hyporheic zone of the flume was measured with a large planar optode. This data package is associated with the publication ’ Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry’ published in Environmental Science and Technology (Turețcaia et al., 2023 https://doi.org/10.1021/acs.est.3c04765). The dataset is comprised of five folders (1) Diss_O2_pic, (2) input_files (3) output_files; (4) python_code; and (5) R_code . Diss_O2_pic contains siximages of dissolved oxygen distribution in a bedform at hours 0, 24, and 72 of the experiment conducted in a large recirculation flume. Images are in separate R and G channels (i.e., RGB). The input_files contains (1) a csv file with FTICR peaks identified within each sample, (2) a csv file with molecular information pertinent to FTICR data with Gibbs free energy calculations adjusted for environmental temperature, (3) a csv file containing concentrations of non-purgeable organic carbon measured throughout the experiment , (4) a csv file containing concentrations of total nitrogen measured throughout the experiment, (5) a csv file containing total biochemical reactions (i.e., transformations) identified in the dataset, (6) a csv containing transformation profiles, and (7) a csv file containing transformations with formulas, and (8) a jpg file with schematic representation of locations for sample collection. The output_files contains (1) and xlsx file containing percent biochemical reactions containing nitrogen identified across all 39 sample, (2) a csv file of merged FTICR data and molecular information files, (3) a csv files containing average Gibbs free energy within sampling domains and at each sampling location, (4) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 0, (5) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 24, (6) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 72, (7) a csv file with percent chemical classes identified across sampling locations at hour 0, (8) a csv file with percent chemical classes identified across sampling locations at hour 24, (9) a csv file with percent chemical classes identified across sampling locations at hour 72, and (10) a csv file containing percent nitrogen containing biochemical reactions identified across sampling locations at hours 0, 24, and 72. The python_code contains seven ipynb files which are Jupyter Notebooks used for data analysis and figures generation. The R_code contains 3 R files with R code used for data analysis and figures generation. This data package contains the processed data used in the associated manuscript. This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PCMDI - An Earth System Model Evaluation Project Lawrence Livermore National Laboratory Annual Report

This annual report describes the activities of PCMDI – An Earth System Model Evaluation Project for the period November 1, 2019 – June 30, 2020. PCMDI is a project at Lawrence Livermore National Laboratory that is funded by the Climate and Environmental Sciences Division (CESD) of the Department of Energy. PCMDI is funded by two efforts within CESD: The Regional and Global Model Analysis program area (Dr. Renu Joseph, program manager) and the Atmospheric Systems Research program (Dr. Shaima Nasiri and Jeffrey Stehr, program managers). As instructed by Drs. Joseph, Nasiri, and Stehr, we provide an annual report addressing sections 4 (Progress and Plans) and 5 (Staffing and Budget Summary) of the SFA Program Management and Performance Reporting Criteria.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

nmrrr : A Reproducible Workflow for Binning and Visualizing NMR Spectra From Environmental Samples

Nuclear magnetic resonance (NMR) spectroscopy is a useful tool for detection and identification of molecular structural information, with increasing applications in environmental sciences. NMR instrument outputs are however heterogeneous and require extensive post-processing, creating barriers to their use and application by non-specialists. Here, we report on a new open-source R package, nmrrr, that processes and visualizes spectral data obtained from one-dimensional solution-state and solid-state NMR experiments; the package also performs relevant calculations commonly applied in natural organic matter communities, such as computing the relative abundance of various functional groups. We document the package's installation, dependencies, and functions; and provide a standard workflow for processing NMR data. This package is currently available on CRAN and GitHub, and community contributions are welcome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mercury Remediation Technology Development for Lower East Fork Poplar Creek—FY 2021 Update

Mercury remediation is a high priority for the US Department of Energy (DOE) Oak Ridge Office of Environmental Management. Mercury contamination in the environment can be found at all three DOE facilities in Oak Ridge, Tennessee, but the greatest environmental risk concern relative to Hg on the Oak Ridge Reservation is likely associated with historical Hg losses at and near the Y-12 National Security Complex (Y-12). Mercury in water and fish from East Fork Poplar Creek (EFPC) downstream of Y-12 exceeds regulatory thresholds. Because of the complexities of Hg transport and fate in the aquatic environment, conventional remedial options for EFPC are highly uncertain. DOE is using a phased adaptive management approach to Hg remediation at Y-12, with a focus in the next few years on construction of the Mercury Treatment Facility (MTF) to treat the most contaminated Y-12 outfall entering EFPC (DOE 2017a; DOE 2017b). Once operational, the MTF will provide additional protection against inadvertent releases of Hg into the stream from decontamination and decommissioning of Y-12 Hg-use buildings. Although the MTF is anticipated to substantially decrease Hg water concentrations and flux in upper EFPC (UEFPC), research and technology development are needed to develop appropriate and longer-term remedial solutions for the downstream environment. Since late 2014, the Oak Ridge Office of Environmental Management and URS | CH2M Oak Ridge LLC/Restoration Services Inc. have supported DOE’s Oak Ridge National Laboratory (ORNL) Environmental Sciences Division staff in conducting field and laboratory studies to develop Hg remedial technology solutions for lower EFPC (LEFPC). Whereas previous annual reporting updates for Hg remediation technology development for LEFPC have focused on presenting detailed results from the previous fiscal year, this FY 2021 update takes a comprehensive, higher-level approach to the research and technology development activities conducted since 2014. The report is organized to be consistent with the three tasks defined in the LEFPC strategic plan

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats

Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Refining Planetary Boundary Layer Height Retrievals From Micropulse‐Lidar at Multiple ARM Sites Around the World

Abstract Knowledge of the planetary boundary layer height (PBLH) is crucial for various applications in atmospheric and environmental sciences. Lidar measurements are frequently used to monitor the evolution of the PBLH, providing more frequent observations than traditional radiosonde‐based methods. However, lidar‐derived PBLH estimates have substantial uncertainties, contingent upon the retrieval algorithm used. In addressing this, we applied the Different Thermo‐Dynamic Stabilities (DTDS) algorithm to establish a PBLH data set at five separate Department of Energy's Atmospheric Radiation Measurement sites across the globe. Both the PBLH methodology and the products are subject to rigorous assessments in terms of their uncertainties and constraints, juxtaposing them with other products. The DTDS‐derived product consistently aligns with radiosonde PBLH estimates, with correlation coefficients exceeding 0.77 across all sites. This study delves into a detailed examination of the strengths and limitations of PBLH data sets with respect to both radiosonde‐derived and other lidar‐based estimates of the PBLH by exploring their respective errors and uncertainties. It is found that varying techniques and definitions can lead to diverse PBLH retrievals due to the inherent intricacy and variability of the boundary layer. Our DTDS‐derived PBLH data set outperforms existing products derived from ceilometer data, offering a more precise representation of the PBLH. This extensive data set paves the way for advanced studies and an improved understanding of boundary‐layer dynamics, with valuable applications in weather forecasting, climate modeling, and environmental studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ESS-DIVE Reporting Format for Location Metadata

The ESS-DIVE location metadata reporting format provides instructions and templates for reporting a minimum set of metadata for discrete point locations in geographic space represented by x, y, and z coordinates. This format was created based on a need for earth and environmental science researchers to more consistently provide metadata about locations where they conduct studies. To create the format, we incorporated elements from ESS-DIVE’s community reporting formats as well as 12 additional data standards or other data resources (e.g., databases, data systems, or repositories). In the template, we ask researchers to indicate unique locations using Location IDs and indicate hierarchies of locations through parent location IDs. We also provide additional optional fields for researchers to indicate how they measured the point location and the date and time that the location was first used as a research siteThis dataset contains support documentation for the reporting format (README.md and instructions.md), a terminology guide (guide.md), a crosswalk indicating how this reporting format relates to existing standards and data resources (Location_metadata_crosswalk.csv), a data dictionary (dd.csv), file-level metadata (flmd.csv), and the location metadata templates in both CSV (Location_metadata_template.csv) and Excel formats (Location_metadata_template.xlsx).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mercury Remediation Technology Development for Lower East Fork Poplar Creek (FY2020 Update)

Mercury (Hg) remediation is a high priority for the US Department of Energy (DOE) Oak Ridge Office of Environmental Management. Mercury contamination in the environment can be found at all three DOE facilities in Oak Ridge, but probably the greatest environmental risk concern relative to Hg on the Oak Ridge Reservation is associated with historical Hg losses at and near the Y-12 National Security Complex (Y-12). Water and fish from East Fork Poplar Creek (EFPC) downstream of Y-12 exceed regulatory thresholds. Because of the complexities of Hg transport and fate in the aquatic environment, conventional remedial options for EFPC are highly uncertain. DOE is using a phased adaptive management approach to Hg remediation at Y-12 with a focus in the next few years on construction of the Mercury Treatment Facility (MTF) to treat the most contaminated Y-12 outfall entering EFPC (DOE 2017a; DOE 2017b). Once operational, the MTF will provide additional protection against inadvertent releases of Hg into the stream from decontamination and decommissioning of Y-12 Hg-use buildings. Although the MTF is anticipated to substantially decrease Hg water concentrations and flux in the upper part of EFPC, research and technology development are needed to develop appropriate and long-term remedial solutions for the downstream environment. Since late 2014, the Oak Ridge Office of Environmental Management and URS | CH2M Oak Ridge LLC/Restoration Services, Inc. have supported DOE’s Oak Ridge National Laboratory (ORNL) Environmental Sciences Division staff in conducting field and laboratory studies to develop Hg remedial technology solutions for lower EFPC (LEFPC). A technology development strategy for LEFPC was developed in 2014 that was consistent with the adaptive management paradigm and DOE’s technology readiness level (TRL) guidelines (Peterson et al. 2015). Initially, a thorough review of the literature was conducted and site-specific information was collected to develop a broad number of potential technologies that might be applied in LEFPC. An adaptive management approach was then used to focus on technologies that might have the most promise and potential remediation benefit. Field and laboratory studies conducted from 2014 to 2020 have identified the major drivers of Hg flux and bioaccumulation in EFPC and narrowed the list of high-merit technologies that might be of use in remediating the downstream environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Aggregation of Leslie matrix models with application to ten diverse animal species

Some grouping is necessary when constructing a Leslie matrix model because it involves discretizing a continuous process of births and deaths. Here, the level of grouping is determined by the number of age classes and frequency of sampling. It is largely unknown what is lost or gained by using fewer age classes, and I address this question using aggregation theory. I derive an aggregator for a Leslie matrix model using weighted least squares, determine what properties an aggregated matrix inherits from the original matrix, evaluate aggregation error, and measure the influence of aggregation on asymptotic and transient behaviors. To gauge transient dynamics, I employ reactivity of the standardized Leslie matrix. I apply the aggregator to 10 Leslie models developed for animal populations drawn from a diverse set of species. Several properties are inherited by the aggregated matrix: (a) it is a Leslie matrix; (b) it is irreducible whenever the original matrix is irreducible; (c) it is primitive whenever the original matrix is primitive; and (d) its stable population growth rate and stable age distribution are consistent with those of the original matrix if the least squares weights are equal to the original stable age distribution. In the application, depending on the population modeled, when the least squares weights do not follow the stable age distribution, the stable population growth rate of the aggregated matrix may or may not be approximately consistent with that of the original matrix. Transient behavior is lost with high aggregation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Can fractal dimensions objectivize gastropod shell morphometrics? A case study from Lake Lugu (SW China)

1. Morphometrics are fundamental for the analysis of size and shape in fossils, particularly because soft parts or DNA are rarely preserved and hard parts such as shells are commonly the only source of information. Geometric morphometrics, that is, landmark analysis, is well established for the description of shape but it exhibits a couple of shortcomings resulting from subjective choices during landmarking (number and position of landmarks) and from difficulties in resolving shape at the level of micro-sculpture. 2. With the aid of high-resolution 3D scanning technology and analyses of fractal dimensions, we test whether such shortcomings of linear and landmark morphometrics can be overcome. As a model group, we selected a clade of modern viviparid gastropods from Lake Lugu, with shells that show a high degree of sculptural variation. Linear and landmark analyses were applied to the same shells in order to establish the fractal dimensions. 3. The genetic diversity of the gastropod clade was assessed. The genetic results suggest that the gastropod clade represents a single species. The results of all morphometric methods applied are in line with the genetic results, which is that no specific morphotype could be delimited. Apart from this overall agreement, landmark and fractal dimension analyses do not correspond to each other but represent data sets with different information. Generally, the fractal dimension values quantify the roughness of the shell surface, the resolution of the 3D scans determining the level. In our approach, we captured the micro-sculpture but not the first-order sculptural elements, which explains that fractal dimension and landmark data are not in phase. 4. We can show that analyzing fractal dimensions of gastropod shells opens a window to more detailed information that can be considered in evolutionary and ecological contexts. We propose that using low-resolution 3D scans may successfully substitute landmark analyses because it overcomes the subjective landmarking. Analyses of 3D scans with higher resolution than used in this study will provide surface roughness information at the mineralogical level. We suggest that fractal dimension analyses of a combination of differently resolved 3D models will significantly improve the quality of shell morphometrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Rapid eco‐phenotypic feedback and the temperature response of biomass dynamics

Biomass dynamics capture information on population dynamics and ecosystem-level processes (e.g., changes in production over time). Understanding how rising temperatures associated with global climate change influence biomass dynamics is thus a pressing issue in ecology. The total biomass of a species depends on its density and its average mass. Consequently, disentangling how biomass dynamics responds to increasingly warm and variable temperatures ultimately depends on understanding how temperature influences both density and mass dynamics. Here, we address this issue by keeping track of experimental microbial populations growing to carrying capacity for 15 days at two different temperatures, and in the presence and absence of temperature variability. We develop a simple mathematical expression to partition the contribution of changes in density and mass to changes in biomass and assess how temperature responses in either one influence biomass shifts. Moreover, we use time-series analysis (Convergent Cross Mapping) to address how temperature and temperature variability influence reciprocal effects of density on mass and vice versa. We show that temperature influences biomass through its effects on density and mass dynamics, which have opposite effects on biomass and can offset each other. We also show that temperature variability influences biomass, but that effect is independent of any effects on density or mass dynamics. Last, we show that reciprocal effects of density and mass shift significantly across temperature regimes, suggesting that rapid and environment-dependent eco-phenotypic dynamics underlie biomass responses. Overall, our results connect temperature effects on population and phenotypic dynamics to explain how biomass responds to temperature regimes, thus shedding light on processes at play in cosmopolitan and abundant microbes as the world experiences increasingly warm and variable temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

δ 2 H isotopic offsets in xylem water measurements under cryogenic vacuum distillation: Quantifying and correcting wood‐water hydrogen exchange influences

Stable isotopes δ 18 O and δ 2 H are used to infer vegetation water sources. In some studies, significant xylem water δ 2 H offsets from potential source waters have been observed. The offsets appear to be more prevalent with cryogenic vacuum distillation (CVD) of plant water. Hypothesized mechanisms for these offsets include changes during plant water uptake and transport, and methodological problems. We propose that a large portion of the offsets are due to hydrogen isotope exchange between xylem water and non-crystalline hydroxyl groups of wood cellulose and hemicellulose during CVD. We present a method for estimating the hypothesized isotopic exchange between wood tissues and water, which is the result of Rayleigh and equilibrium fractionation. To estimate the exchange, we use published wood properties for North American tree species and isotope chemical relationships as a function of moisture content, CVD temperature and water extraction efficiency. A simple model of exchange between xylem water and hydroxyl groups captures the range of observations in studies in which CVD and non-CVD methods were compared. To evaluate the model, we compared observed δ 2 H offsets (sw-excess) values from two field datasets (90°C, n = 364, and 170°C, n = 43) to δ 2 H offsets estimated with our chemical model. We found good agreement between observed and estimated δ 2 H offsets for samples extracted at 90°C (r 2 = 0.69) but not for samples extracted at 170°C (r 2 = 0.20). The offset may be eliminated by increasing the extraction temperature to 229°C or by adding a standard sufficient to raise the moisture content to >150%. A correction can also be approximated by applying a theoretical calculation based on the extraction temperature, moisture content and water extraction efficiency.

54 ENVIRONMENTAL SCIENCES↗