News & Media
Dryland Expansion Regulates Variability in Plant Biodiversity
Model shows quantified impact of accelerated dryland expansion on its productivity
Drylands, such as grasslands, savannas, and deserts, are expected to expand and become more arid at an accelerating rate over the next century. The effects of this expansion and degradation on their gross primary production (GPP) remain elusive. A recent paper in Nature Communications is the first to quantify the impact of accelerated dryland expansion on their productivity. In addition, as different subtypes of drylands expand and convert, large changes will be seen in how regional and subtypes contribute to variability in global dryland productivities.
Drylands are the largest source of interannual variability in the global carbon sink. Any changes in dryland ecosystems under climate change would have large implications for global carbon cycle. This work improves our understanding of how accelerated dryland expansion impacts the productivity of drylands. Dryland expansion and climate-induced conversions among sub-humid, semi-arid, arid, and hyper-arid subtypes will lead to substantial changes in regional and subtype contributions to global dryland GPP variability.
Drylands, such as grasslands, savannas, and deserts, cover approximately 41% of the Earth’s land surface and support more than 38% of the global population. Global dryland ecosystems with high plant productivity account for approximately 40% of global land net primary production (NPP.) They also act as the dominate global land CO2 sink and, over recent decades, have contributed the largest amount of net CO2 flux affecting interannual variability.
To study the impact of accelerated dryland expansion and degradation on global dryland GPP, researchers from Washington State University and Pacific Northwest National Laboratory assessed MODIS GPP data from 2000-2014 and the CMIP5 aridity index (AI.) Results from the investigation shows a positive relationship between GPP and AI over dryland regions, with total dryland GPP increasing by the end of the 21st century by 12 ± 3% relative to 2000–2014 increases. However, GPP per unit dryland area will decrease with degradation of drylands. Such expansion and conversions among different subtypes of drylands will lead to large changes in regional and subtype contributions to variability in global dryland productivity.
Researchers in this study used a cubic fitting method to find the relationship between dryland GPP and CMIP5 AI data. With long-term GPP data, they analyzed the trend and interannual variability of dryland GPP into the future. To verify the accuracy of projected GPP data, the team compared projected GPP data to GPP data from 15 CMIP5 models. The results showed agreement with the modeling data in eight regions during the same period.
Dynamic Earth system models are essential to more fully understand dryland ecosystem–climate interactions.
This work is supported by the U.S. Department of Energy (DOE) Office of Science, Biological and Environmental Research (BER) program as part of BER’s Subsurface Biogeochemical Research Program (SBR) at the Pacific Northwest National Laboratory (PNNL.) We also acknowledge support by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP), Grant No. 2019QZKK0602, the National Natural Science Foundation of China under grants 41521004, 41991231 and 41975075, the Foundation of Key Laboratory for Semi-Arid Climate Change of the Ministry of Education in Lanzhou University, the China 111 Project (No. B13045), the Fundamental Research Funds for the Central Universities (lzujbky-2017-it18.)
Yao, J., Liu, H., Huang, J., Gao, Z., Wang, G., Li, D., Yu, H., Chen, X. 2020. Accelerated dryland expansion regulates future variability in dryland gross primary production. Nature Communications, (2020) 11:1665 | https://doi.org/10.1038/s41467-020-15515-2.
NWRTC Notes From the Field (June 2020)
Interviews with public health professionals who are helping to keep us safe
PNNL's Northwest Regional Technology Center interviews Assistant Chief of Resource Management for Seattle Fire Department Willie Barrington about how his team faced the unknown when the COVID-19 pandemic hit Seattle, Washington.
When a pinch is problematic: Detecting pertechnetate in groundwater
PNNL develops an effective tool for measuring a tricky contaminant
Imagine trying to detect and measure a pinch of salt in an Olympic-size swimming pool. Now pretend the tools you are using don’t work well. Some can detect the salt but can’t tell you how much is in there, and others confuse salt with chlorine.
Now swap the swimming pool for a source of groundwater and the salt for a radioactive contaminant called pertechnetate.
Pertechnetate is a byproduct of nuclear waste. If it ends up where it is not supposed to be—like, in groundwater—it could impact human health, which is why researchers and regulators keep a close lookout for it. The environmental safety limits for pertechnetate are roughly equivalent to a pinch of salt in an Olympic pool. And there are only a few technologies to measure it, each with limitations.
PNNL research tackles this challenge with new technology to detect and accurately measure pertechnetate at super low levels in groundwater. This research, “Redox-Based Electrochemical Affinity Sensor for Detection of Aqueous Pertechnetate Anion,” was the cover article for the March 2020 edition of ACS Sensors (DOI: 10.1021/acssensors.9b01531).
Why it matters: The Environmental Protection Agency drinking water standard for pertechnetate is 0.000000052 grams per liter (that’s roughly 1/6000th the weight of a single poppy seed). While techniques exist for detection of pertechnetate in the environment, many have their drawbacks. PNNL’s technology can accurately measure low levels of pertechnetate in groundwater. Additionally, this proof of concept has the potential to be applied to other target contaminants simultaneously, increasing efficiency for environmental sensing.
Summary: The new technology acts like a coin counter, but at a microscopic level. It sorts one type of chemical from another, providing the total amount of a target chemical at the end. The tool uses custom probes with a gold electrode that only allows the target groundwater contaminants to stick while the other chemicals bounce off.
Sulfur likes to bind to gold and it also tends to react with pertechnetate, making sulfur-containing compounds an ideal intermediate in tool development. The sulfur sticks to the gold probe, then reacts with the pertechnetate, which forms a precipitate. The precipitate inhibits an electric current pulsing through the probe, providing an inverse measurement of pertechnetate concentration.
What’s Next: While this work was specifically focused on pertechnetate, there is potential to expand the technology to simultaneous multiple targets with the goal of increasing the efficiency of environmental measurements.
Sponsors: This research was funded by the Laboratory Directed Research and Development program at PNNL and by the Deep Vadose Zone program under the U.S. Department of Energy’s (DOE’s) Office of Environmental Management. Part of this research was performed at the Environmental Molecular Sciences Laboratory, a national user facility at PNNL managed by the DOE Office of Biological and Environmental Research.
PNNL Research Team: Sayandev Chatterjee, Meghan S. Fujimoto, Yingge Du, Gabriel B. Hall, Nabajit Lahiri, Eric D. Walter, Libor Kovarik. ACS Sensors cover illustration by Rose Perry, PNNL.
Tracking the Behavior of a Uranium Plume
Field research coupled with three-dimensional modeling are used to predict how groundwater and river exchange influence a contaminant plume.
A recent paper published in Water Resources Research found that the spatial variability of subsurface sediments, and seasonal fluctuations in a river’s water level, influences the behavior of a uranium contaminant plume, particularly in rivers influenced by dams.
The research team created a complex numerical model and ran a 5-year simulation of the exchange between surface water and groundwater in a portion of the Columbia River at the Hanford Site. Model accuracy was evaluated using detailed water sampling data from the site, distributed in space and time. Both the model and data from site samples showed that the uranium can travel via multiple paths of river water and groundwater exchange.
Predicting and modeling the evolution of a contaminant plume in a river corridor subject to rising and falling water levels from upstream dam operations is challenging. Factors such as seasonal dam discharge variation, the permeability of surface and subsurface materials, and changes in water chemistry, make river corridors a complex environment to study. This study is one of a few that have used a highly detailed three-dimensional modeling approach to simulate the migration of contaminants as influenced by the hydrologic exchanges between surface and subsurface waters at a large spatial scale. High-resolution monitoring, to ground truth the model’s accuracy, provided researchers a robust evaluation of the model’s predictive capabilities. Ultimately, the methods and findings in this study provide a foundation for designing future modeling and monitoring research to assist in environmental management and decision making.
A team of scientists led by John Zachara of Pacific Northwest National Laboratory examined the impact of river water and groundwater exchange in relation to a uranium contaminant plume migration at Hanford, Washington. The goal was to develop and improve the predictive understanding of hydrologic exchange flows and their role in changing river corridor biogeochemistry.
The team used an innovative combination of field sampling and three-dimensional mathematical models to investigate how river stage variation over seasons and subsurface hydrogeology interact to influence subsurface contaminant migration. In this work, the authors note that there are very few studies that model solute transport or plume behavior during dynamic hydrologic exchange in large river corridors, and that the model they developed can be applied to other, similar riverine systems.
According to both their model and data, river water exchange with groundwater in large, gravel-bed river corridors may create a wide interaction zone, which is different from most headwater systems. Water level variations in dam-regulated river corridors lead to changing flow directions, velocities, and sediment compositions, that influence contaminant plume behavior. The residence time and transport distance of intruded river water is controlled by both river stage and subsurface hydrogeologic features.
Funded by the Department of Energy’s Biological and Environmental Research (BER) program, this work addresses DOE’s mission to improve the predictive understanding of how watershed systems respond to environmental perturbations caused by changes in water availability/quality, land use/vegetation cover, and inorganic element/contaminant loading. Researchers used the DOE-funded NERSC, National Energy Research Scientific Computing Center, user facility in their model development.
John Zachara, Pacific Northwest National Laboratory, email@example.com
This research was supported by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research Program, as part of the Subsurface Biogeochemical Research Scientific Focus Area (SFA) at Pacific Northwest National Laboratory (PNNL).
J.M. Zachara, C. Xingyuan, S. Xuehang, P. Shuai, C. Murray, C. T. Resch. “Kilometer‐scale hydrologic exchange flows in a gravel‐bed river corridor and their implications to solute migration.” Water Resources Research, e02851-18 (2020). DOI: 10.1029/2019WR025258
Microbial diversity influences nitrogen cycling in rivers
Seasonal changes affect microbiome communities, genes, and subsurface biogeochemical pathways differently
DOE researchers investigated the role of microbial genetic diversity in two major subsurface biogeochemical processes: nitrification and denitrification. Results show that across different seasons only a few microbe species, namely Nitrosoarchaeum, carry out nitrification functions—demonstrating high resistance to environmental change. However, denitrification genes, which are more broadly distributed in the community, displayed a variety of diversity patterns and abundance dynamics—demonstrating greater microbial interactions as conditions change.
There is little research connecting microbiomes at the genetic level to hydrobiogeochemical modeling. This research helps broaden collective knowledge for a better understanding of the pathways affected by environmental changes. For example, under extreme environmental conditions an entire biochemical pathway could be altered or eliminated if a single step has low genetic diversity such that its loss could not be replaced.
The Pacific Northwest National Laboratory research team, led by Bill Nelson, found that major environmental processes—specifically nitrification and denitrification—are maintained through a variety of diversity strategies. Historically, the bulk of biogeochemical research has focused on microbial communities at the organismal level. But this research focused on the importance of genetic distribution and diversity.
In their recent PLoS ONE paper, the researchers discuss the roles microbes play in ecological functions; the novelty of the genetic makeup of these microbes; and future research opportunities to determine which organisms are genetically expressing nitrogen cycling functions.
The novelty of this study comes from examining the temporal dynamics of diversity at the gene level. To evaluate all genes in the nitrification and denitrification pathways, novel Hidden Markov Models (HMMs) were developed that can recognize the broad diversity found in environmental samples. They found that while different environmental conditions impair microbiome growth and the gene expression of some populations, at the same time, it can stimulate others. High biodiversity at the organism or genetic level creates more resiliency, and the microbiome community can respond more rapidly to environmental changes.
Bill Nelson, Pacific Northwest National Laboratory, William.Nelson@pnnl.gov
This research was supported by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research Program, as part of the Subsurface Biogeochemical Research Scientific Focus Area (SFA) at Pacific Northwest National Laboratory (PNNL).
W.C. Nelson, E.B. Graham, A.R. Crump, S.J. Fansler, E.V. Arntzen, D.W. Kennedy, J.C. Stegen, “Distinct temporal diversity profiles for nitrogen cycling genes in a hyporheic microbiome”. PLoS ONE 15(1) e0228165 (2020). [DOI: 10.1371/ journal.pone.0228165]
Oxide interfaces in disarray
Exploration of disorder at material interfaces could lead to better device performance
The structure of an interface at which two materials meet helps determine the performance of the computers and other devices we use every day. However, understanding and controlling interface disorder at the atomic level is a difficult materials science challenge.
A research team at PNNL and Texas A&M University combined cutting edge imaging and numerical simulations to examine disordering processes in widely used oxide materials. They found that certain oxide interface configurations remain stable in extreme environments, suggesting ways to build better performing, more reliable devices for fuel cells, space-based electronics, and nuclear energy.
Visualizing the disordering process
As reported in Advanced Materials Interfaces (“Asymmetric Lattice Disorder Induced at Oxide Interfaces,” DOI: 10.1002/admi.201901944) the team set out to examine interfaces between pyrochlore-like and perovskite oxides, two common classes of functional materials used in energy and computing technologies. While most past work has focused on individual bulk materials, less attention has been paid to interfaces connecting them, as would be the case in a device. In particular, it is not clear how interface features, such as composition, bonding, and possible defects, govern disordering processes.
Funded by PNNL’s Nuclear Process Science Initiative (NPSI), the team employed experimental and theoretical methods to study the interface at different stages of disorder introduced through ion irradiation. They imaged the local structure of the material using high-resolution scanning transmission electron microscopy and convergent beam electron diffraction, which showed that the bulk of the two materials disordered (amorphized) before the interface. After further irradiating the material, they found that a band region near the interface had remained crystalline, while the rest of the structure had become amorphous.
To understand this behavior, the team turned to a technique called electron energy loss spectroscopy, which allowed them to examine the atomic-scale chemistry and defects formed at the interface. Their measurements revealed the presence of substantial amounts of defects called oxygen vacancies, which can greatly affect properties such as magnetism and conductivity. Based on these observations, the team constructed a theoretical model of the interface and explored the effect of different interface configurations on the tendency to form vacancies.
“In our model we are able to systematically vary interface features, such as crystal structure, intermixing, and strain, to see their effect on defect formation. We found that the structure of the materials on both sides of the interface can influence where defects are likely to form first,” explained Steven R. Spurgeon, a PNNL materials scientist. “Our model suggests that by selecting appropriate crystal structures and controlling how they connect, it may be possible to dictate the sequence of defect formation, which would allow us to enhance the properties of these materials.”
The team is exploring other interface structures and chemistries, with an eye toward improving the performance of oxides used in extreme environments.
The study was conducted as part of the NPSI project, “Damage Mechanisms and Defect Formation in Irradiated Model Systems,” led by Spurgeon.
Creating better models to predict subsurface water flow and transport
New framework improves the predictions of subsurface sediment permeability
Co-authors of a paper in Water Resources Research led by PNNL researchers developed a new iterative data assimilation framework to more accurately describe the permeability of subsurface sediments in numerical models when using facies, a system that classifies dissimilar sediments into distinct geological units that share important features of interest to modelers. The iterative framework applies data from field observations and experiments to inform the delineation of facies at the start of each model run. Further refinements are achieved at each iteration through the application of statistical constraints that maintain geologic continuity among adjacent locations.
Spatial distribution of three facies (red, yellow and blue colors) in a 2D vertical cross section of a 3D case. Figures show the new method provides a more accurate and continuous estimation of facies distribution compared to the conventional method. White colors in the figures are bore samples and black dots are the conditioning points selected by the new method.
More realistic numerical representations of the permeability of subsurface sediments lead to improved predictions of groundwater flow and the concentration of constituents that are transported with the flow. The data assimilation framework can also be applied to estimate other subsurface properties from field measurements, or from data from other systems such as watersheds, as long as they can be categorized into a few discrete representative units.
Observational data on subsurface permeability is limited for most watersheds because of the impracticality of digging enough boreholes or wells to capture the heterogeneous nature of the subsurface environment. To solve for this limitation, researchers have widely adopted approaches that estimate permeability from field experiments such as a) measuring how water levels at a cluster of wells change when water is pumped at a nearby well, or b) monitoring how quickly a tracer released at one well reaches other wells in the aquifer. The U.S. Department of Energy’s Hanford 300 Area Integrated Field Research Challenge site, for example, is well characterized from data assimilation methods that were used to understand the long-term persistence of nuclear fuel fabrication wastes disposal from 1943 to 1975.
The use of a facies approach to segment the subsurface reduces complexity in numerical models by grouping heterogeneous sediments into distinct homogenous units defined by hydraulic, physical and or chemical properties. A major difficulty with existing facies-based approaches in numerical models is that each facies is treated as its own, independent unit. Therefore, these models fail to capture the spatial continuity of subsurface sediments. The authors of this paper developed a framework that maintains continuity between neighboring facies in numerical models and thus better reflects true subsurface geology, and thereby groundwater movement. The improvements come from an iterative data assimilation approach that incorporates direct and indirect data about subsurface permeability gathered from field observations and experiments at the start of each model run as well as the application of statistical constraints about subsurface geology. The data assimilation and statistical constraint steps are re-imposed for each iteration, leading to refined facies delineation. This framework reduces uncertainty about the spatial distribution of sediment types in the subsurface, which results in more accurate predictions of groundwater flow and constituent transport.
The authors evaluated the performance of the new framework on a two-dimensional, two-facies model and a three-dimensional, three-facies model of DOE’s well-characterized Hanford 300 Area that were conceptualized from borehole and field tracer experiments. The results of the research shows that the framework can identify facies spatial patterns and reproduce tracer breakthrough curves with much improved accuracy over facies-based approaches that lack spatial continuity constraints. With additional data, the authors say that the framework can also be used to categorize biogeochemical reactive units in an aquifer.
Xingyuan Chen, Earth Scientist, Xingyuan.Chen@pnnl.gov
Funding for this research came from DOE Office of Science BER, PNNL Subsurface Biogeochemical Research SFA.
Song, X., Chen, X., Ye, M., Dai, Z., Hammond, G., And Zachara, J.M. (2019). Delineating facies spatial distribution by integrating ensemble data assimilation and Indicator Geostatistics with level-set transformation. Water Resources Research, 55. https://doi.org/10.1029/2018WR023262
Improving nuclear waste storage models by studying the chemistry of material interactions
WastePD EFRC research on the glass-steel interface was published in Nature Materials
New research unravels the chemistry of how materials in the waste packages used for the disposal of high-level radioactive waste interact in deep geologic repository environments. Having a better understanding of the interactions between materials under various conditions provides more information to make waste storage performance models more robust.
“Many performance models use conservative approaches such as assuming that the steel canister walls don’t even exist or that they dissolve very fast. This study provides the opportunity to better incorporate the canister barrier in the models,” said Joseph Ryan, a PNNL materials scientist and coauthor on the paper, “Self-accelerated corrosion of nuclear waste forms at material interfaces,” published in Nature Materials.
The United States is converting highly radioactive nuclear waste, also known as high-level waste, into glass. The molten glass is poured into steel canisters for long-term storage and ultimate disposal in a geologic repository. The goal is to design waste storage and disposal systems that would remain safe for hundreds of thousands of years to come, even if they are exposed to water. Because of the extensive time span of waste storage, researchers turn to cutting-edge science to project what will happen during that time period. The data is used to inform extensive safety analyses—helping make sure the system is engineered to be compatible with the natural system so that waste remains separate from the environment.
“We can’t just do a test on a material and say, ‘That material corroded this much in 30 days and extrapolate that to a million years.’ It doesn’t work that way,” Ryan said. “At the most basic level, we try to understand the underlying chemistry of corrosion. Then, we feed that information into computer models to calculate the expected release over time.”
In this study, led by the WastePD Energy Frontier Research Center based at Ohio State University, researchers unpacked the chemistry that occurs when two materials are close together, focusing on glass-steel along with ceramic-steel interactions. This chemical situation could occur when water has percolated into the repository and has breached the steel canister, exposing the glass-steel interface to water.
When water finally breaches the waste package container, it will fill the microscopic space that forms between the solid glass and the steel canister. Chemical reactions that happen in localized and tiny microenvironments such as these can be quite different than those happening in a more open setting. In this case, this localized area can have a different chemistry than the surrounding solution, causing more corrosion than would be expected.
The researchers tested their theory in the laboratory. They pressed glass and steel together in salty liquid and kept it at 90° C (194° F) for a month. At the end of the experiment, they found differences in the width of thin layers that indicated higher corrosion between the glass-steel couple interface than in a control sample.
Why it matters: This research allows scientists to improve models that project how a disposal canister could perform in a deep geologic environment. Having a better understanding of the interactions between materials under various conditions provides more information to make the models more robust. Currently, some models project what happens to waste under the assumption that the steel canister walls do not exist. Operating under this pretext can result in higher projections of waste degradation than would likely occur when taking a conservative approach. But better understanding the chemistry of how the solid waste and the steel canister interact allows a scientifically based understanding of how the canisters behave and interact with the glass to be included in performance assessment models.
Summary: High-level waste is immobilized as glass in stainless steel canisters. On cooling, a confined crevice space forms at the stainless steel-glass interface. If the disposal canister is breached and if water can enter the steel-glass interface, it could result in anodic dissolution of the stainless steel, generating metal cations, which hydrolyze to form protons and strongly increase the local acidity. This acidic environment may locally enhance the corrosion of both the stainless steel and the glass, which leads to the release of cations from the glass. Further, the coupled corrosion may trigger the precipitation of additional secondary phases that may impact subsequent canister corrosion or nuclear glass durability.
What’s Next: While this study sheds light on the chemical interactions that occur at the stainless steel-glass interface, there are more interactions to explore. Ultimately, a better understanding of different chemical mechanisms will improve the overall performance model.
Sponsors: This work was supported as part of the Center for Performance and Design of Nuclear Waste Forms and Containers, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Basic Energy Sciences under Award no. DESC0016584.
Research Team: Xiaolei Guo, Gerald S. Frankel, Gopal Viswanathan, Tianshu Li (Ohio State University); Stéphane Gin (CEA, France); Penghui Lei, Tiankai Yao, Jie Lian (Rensselaer Polytechnic Institute); Hongshen Liu, Dien Ngo, Seong H. Kim (Pennsylvania State University); Daniel K. Schreiber, John D. Vienna, Joseph V. Ryan (PNNL); Jincheng Du (University of North Texas)