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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration

Wearable silicone wristbands are a rapidly growing exposure assessment technology that offer researchers the ability to study previously inaccessible cohorts and have the potential to provide a more comprehensive picture of chemical exposure within diverse communities. However, there are no established best practices for analyzing the data within a study or across multiple studies, thereby limiting impact and access of these data for larger meta-analyses. We utilize data from three studies, from over 600 wristbands worn by participants in New York City and Eugene, Oregon, to present a first-of-its-kind manuscript detailing wristband data properties. We further discuss and provide concrete examples of key areas and considerations in common statistical modeling methods where best practices must be established to enable meta-analyses and integration of data from multiple studies. Finally, we detail important and challenging aspects of machine learning, meta-analysis, and data integration that researchers will face in order to extend beyond the limited scope of individual studies focused on specific populations.

Bramer, Lisa M.↗
DOE OSTI2025

Turbidity and suspended sediment data for Gwynns Falls, Baisman Run, and Pond Branch, Baltimore County and Baltimore City, MD, USA

This resource includes turbidity and suspended sediment data collected at two sampling stations located on Gwynns Falls in Baltimore County, MD, USA. In addition, two forested reference sites, Baisman Run and Pond Branch at Oregon Ridge, and two urban sites, Dead Run and Maiden's Choice Run (tributaries to Gwynns Falls), were sampled in Baltimore County and Baltimore City, MD, USA. Turbidity sensor data were collected at a 5-minute frequency using YSI EXO2 sondes. Suspended sediment was collected using ISCO samplers for the purpose of establishing correlations between turbidity and suspended sediment concentration. The six sites are co-located with USGS stream gages. This resource is part of the Baltimore Social-Environmental Collaborative Urban Integrated Field Laboratory supported by Department of Energy as well as the Critical Zone Collaborative Network supported by National Science Foundation. This resource includes a technical report summarizing the findings.

58 GEOSCIENCES↗
DOE OSTI2017

Spatiotemporal Variability of Turbulence Kinetic Energy Budgets in the Convective Boundary Layer over Both Simple and Complex Terrain

The assumption of sub-grid scale (SGS) horizontal homogeneity within a model grid cell, which forms the basis of SGS turbulence closures used by mesoscale models, becomes increasingly tenuous as grid spacing is reduced to a few kilometers or less, such as in many emerging high-resolution applications. Herein, we use the turbulence kinetic energy (TKE) budget equation to study the spatio-temporal variability in two types of terrain—complex (Columbia Basin Wind Energy Study [CBWES] site, north-eastern Oregon) and flat (ScaledWind Farm Technologies [SWiFT] site, west Texas) using the Weather Research and Forecasting (WRF) model. In each case six-nested domains (three domains each for mesoscale and large-eddy simulation [LES]) are used to downscale the horizontal grid spacing from 10 km to 10 m using the WRF model framework. The model output was used to calculate the values of the TKE budget terms in vertical and horizontal planes as well as the averages of grid cells contained in the four quadrants (a quarter area) of the LES domain. The budget terms calculated along the planes and the mean profile of budget terms show larger spatial variability at CBWES site than at the SWiFT site. The contribution of the horizontal derivative of the shear production term to the total production shear was found to be 45% and 15% of the total shear, at the CBWES and SWiFT sites, respectively, indicating that the horizontal derivatives applied in the budget equation should not be ignored in mesoscale model parameterizations, especially for cases with complex terrain with <10 km scale.

convective boundary layer↗
DOE OSTI2019

Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin

Annually and seasonally averaged wind profiles from three Doppler lidars were gathered from sites in the Columbia River basin of east-central Oregon and Washington, a major region of wind-energy production, for the Second Wind Forecast Improvement Project (WFIP2) experiment. The profile data are used to quantify the spatial variability of wind flows in this area of complex terrain, to assess the HRRR-NCEP model's ability to capture spatial and temporal variability of wind profiles, and to evaluate model errors. Annually averaged measured wind speed differences over the 70-km extent of the lidar measurements reached 1 m s -1 within the wind-turbine rotor layer, and 2 m s -1 for 200-500 m AGL. Stronger wind speeds in the lowest 500 m occurred at sites higher in elevation, farther from the river, and farther west - closer to the Cascade Mountain barrier. Validating against the lidar data, the HRRR model underestimated strong wind speeds (>12 m s -1 ) and, consequently, their frequency of occurrence, especially at the two lowest-elevation sites, producing annual low biases in rotor-layer wind speed of 0.5 m s -1 . The RMSE between measured and modeled winds at all sites was about 3 m s -1 and did not degrade significantly with forecast lead time. The nature of the model errors was different for different seasons. Furthermore, although the three sites were located in the same basin terrain, the nature of the model errors was different at each site. Thus, if only one of the sites had been instrumented, different conclusions would have been drawn as to the major sources of model error, depending on where the measurements were made.

17 WIND ENERGY↗
DOE OSTI2022

A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin–Obukhov similarity; and (ii) a modified Priestley–Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Measurements and Model Improvement: Insight into NWP Model Error Using Doppler Lidar and Other WFIP2 Measurement Systems

Abstract Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s −1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement. Significance Statement Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.

Meteorology & Atmospheric Sciences↗
DOE OSTI2018

Predicting Large Ocean Wave Events Characterized by Bimodal Energy Spectra in the Presence of a Low-Level Southerly Wind Feature

Abstract Three large wave events are simulated with WaveWatch III using different wind inputs and physics packages. The modeled output, including spectral shape and bulk parameter time series, are compared with National Data Buoy Center buoy observations offshore of Newport, Oregon. The atmospheric conditions that generate these large waves include a strong southerly wind along with a distant cyclone. The energetic contributions of these simultaneously occurring atmospheric features result in a wave field characterized by bimodal energy spectra for two events and unimodal energy spectra for the third event. The analysis of model output evaluates bulk parameter time series of significant wave height, mean period, and mean wave direction derived from partitioned energy spectra. A consistent underestimation in wave energy approaching from the southwestern direction is found for the output associated with all model configurations. This wave energy is generated by the southerly wind. An overestimation in swell energy approaching from the northwest is also found for all model configurations. The model configuration that most accurately reproduces the southerly wave energy results in the best performance for the overall bulk parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Doppler-Lidar Evaluation of HRRR-Model Skill at Simulating Summertime Wind Regimes in the Columbia River Basin during WFIP2

Complex-terrain locations often have repeatable near-surface wind patterns, such as synoptic gap flows and local thermally forced flows. An example is the Columbia River Valley in east-central Oregon-Washington, a significant wind-energy-generation region and the site of the Second Wind-Forecast Improvement Project (WFIP2). Data from three Doppler lidars deployed during WFIP2 define and characterize summertime wind regimes and their large-scale contexts, and provide insight into NWP model errors by examining differences in the ability of a model [NOAA’s High-Resolution Rapid-Refresh (HRRR-version1)] to forecast wind-speed profiles for different regimes. Seven regimes were identified based on daily time series of the lidar-measured rotor-layer winds, which then suggested two broad categories. First, in three regimes the primary dynamic forcing was the large-scale pressure gradient. Second, in two regimes the dominant forcing was the diurnal heating-cooling cycle (regional sea-breeze-type dynamics), including the marine intrusion previously described, which generates strong nocturnal winds over the region. The other two included a hybrid regime and a non-conforming regime. For the large-scale pressure-gradient regimes, HRRR had wind-speed biases of ~1 m s -1 and RMSEs of 2-3 m s -1 . Errors were much larger for the thermally forced regimes, owing to the premature demise of the strong nocturnal flow in HRRR. Thus, the more dominant the role of surface heating in generating the flow, the larger the errors. Major errors could result from surface heating of the atmosphere, boundary-layer responses to that heating, and associated terrain interactions. Finally, measurement/modeling research programs should be aimed at determining which modeled processes produce the largest errors, so those processes can be improved and errors reduced.

17 WIND ENERGY↗
DOE OSTI2025

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2019

Exome resequencing and GWAS for growth, ecophysiology, and chemical and metabolomic composition of wood of Populus trichocarpa

Populus trichocarpa is an important forest tree species for the generation of lignocellulosic ethanol. Understanding the genomic basis of biomass production and chemical composition of wood is fundamental in supporting genetic improvement programs. Considerable variation has been observed in this species for complex traits related to growth, phenology, ecophysiology and wood chemistry. Those traits are influenced by both polygenic control and environmental effects, and their genome architecture and regulation are only partially understood. Genome wide association studies (GWAS) represent an approach to advance that aim using thousands of single nucleotide polymorphisms (SNPs). Genotyping using exome capture methodologies represent an efficient approach to identify specific functional regions of genomes underlying phenotypic variation. We identified 813 K SNPs, which were utilized for genotyping 461 P. trichocarpa clones, representing 101 provenances collected from Oregon and Washington, and established in California. A GWAS performed on 20 traits, considering single SNP-marker tests identified a variable number of significant SNPs ( p -value < 6.1479E-8) in association with diameter, height, leaf carbon and nitrogen contents, and δ 15 N. The number of significant SNPs ranged from 2 to 220 per trait. Additionally, multiple-marker analyses by sliding-windows tests detected between 6 and 192 significant windows for the analyzed traits. The significant SNPs resided within genes that encode proteins belonging to different functional classes as such protein synthesis, energy/metabolism and DNA/RNA metabolism, among others. SNP-markers within genes associated with traits of importance for biomass production were detected. They contribute to characterize the genomic architecture of P. trichocarpa biomass required to support the development and application of marker breeding technologies.

09 BIOMASS FUELS↗
DOE OSTI2023

Characterizing post-fire delayed tree mortality with remote sensing: sizing up the elephant in the room

Abstract Background Despite recent advances in understanding the drivers of tree-level delayed mortality, we lack a method for mapping delayed mortality at landscape and regional scales. Consequently, the extent, magnitude, and effects of delayed mortality on post-fire landscape patterns of burn severity are unknown. We introduce a remote sensing approach for mapping delayed mortality based on post-fire decline in the normalized burn ratio (NBR). NBR decline is defined as the change in NBR between the first post-fire measurement and the minimum NBR value up to 5 years post-fire for each pixel. We validate the method with high-resolution aerial photography from six wildfires in California, Oregon, and Washington, USA, and then compare the extent, magnitude, and effects of delayed mortality on landscape patterns of burn severity among fires and forest types. Results NBR decline was significantly correlated with post-fire canopy mortality (r 2 = 0.50) and predicted the presence of delayed mortality with 83% accuracy based on a threshold of 105 NBR decline. Plots with NBR decline greater than 105 were 23 times more likely to experience delayed mortality than those below the threshold (p < 0.001). Delayed mortality occurred across 6–38% of fire perimeters not affected by stand-replacing fire, generally affecting more areas in cold (22–41%) and wet (30%) forest types than in dry (1.7–19%) types. The total area initially mapped as unburned/very low-severity declined an average of 38.1% and generally persisted in smaller, more fragmented patches when considering delayed mortality. The total area initially mapped as high-severity increased an average of 16.2% and shifted towards larger, more contiguous patches. Conclusions Differences between 1- and 5-year post-fire burn severity maps depict dynamic post-fire mosaics resulting from delayed mortality, with variability among fires reflecting a range of potential drivers. We demonstrate that tree-level delayed mortality scales up to alter higher-level landscape patterns of burn severity with important implications for forest resilience and a range of fire-driven ecological outcomes. Our method can complement existing tree-level studies on drivers of delayed mortality, refine mapping of fire refugia, inform estimates of habitat and carbon losses, and provide a more comprehensive assessment of landscape and regional scale fire effects and trends.

Environmental Sciences & Ecology↗
DOE OSTI2018

Public Acceptance of Pre-Commercial Thinning and Energy and Soil Amendment Products from Post-Harvest Residues in Western Forests of the United States

Abstract . The goals of the Waste-to-Wisdom project is to produce bioenergy products and biochar from post-harvest forest residues and thus understanding public acceptance of the forest management and utilizing forest residues for biomass-based products is critical. This research explores the public perceptions of producing bioenergy products and biochar from forest thinning activities in the western Pacific Northwest region. A web-based survey was conducted in Washington, Oregon, and Northern California generating 1,202 responses. Multinomial regression techniques and simulation-based approach were applied to analyze how demographic and socio-economic factors influence public perceptions. People living in less populated areas are more likely to support forest thinning. Higher levels of education and household income also lead to higher levels of support for forest thinning. On the other hand, supports for forest thinning results in supports for using forest residuals to produce bioenergy products. These results suggest that different strategies are necessary to effectively communicate the environmental and ecological benefits of using forest residuals derived from forest thinning activities to produce biomass-based products. Keywords: Environmental Perceptions, Multinomial Logistic Regression, Natural Resource Management, Rural vs. Urban, Simulation-Based Approach.

Agriculture↗
DOE OSTI2018

Resistance to an eriophyid mite in an interspecific hybrid pedigree of Populus

Schizoempodium mesophyllincola is an eriophyid mite that feeds in leaves of Populus trichocarpa in the central part of this cottonwood tree’s range (i.e., coastal British Columbia, Washington and Oregon) in the Pacific Northwest (PNW) of North America, and on some interspecific hybrids planted in short-rotation, intensive forestry in the region. The mite, a leaf vagrant, sucks the contents of spongy mesophyll cells, causing leaf discoloration, or “bronzing.” Here, we investigate the inheritance pattern of resistance to leaf bronzing using a three-generation Populus trichocarpa x P. deltoides hybrid pedigree. We found that resistance to the mite is an exaptation in that its source in two related F 2 families of the TxD hybrid pedigree was the non-native host, P. deltoides . Two grandparental genotypes of the latter, ‘ILL-5’ and ‘ILL-129’, were completely free of the bronzing symptom and that phenotype was inherited in a Mendelian manner in the F 1 and F 2 . Resistance to S. mesophyllincola is similar to resistance to many other regional pathogens of P. trichocarpa (e.g., Melampsora occidentalis, Venturia inopina, Sphaerulina populicola, and Taphrina sp. ) in that it is inherited from the non-native grandparent (e.g., P. deltoides, P. nigra, or P. maximowiczii ) in three-generation, hybrid pedigrees. In addition to finding evidence for Mendelian inheritance, we found two QTLs with LOD scores 5.03 and 3.12 mapped on linkage groups (LG) III and I, and they explained 6.7 and 4.2% of the phenotypic variance, respectively. The LG I QTL is close to, or synonymous with, one for resistance to sap-feeding arthropods and leaf developmental traits as expressed in a British study utilizing the same pedigree.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Phylogenetic diversity of 200+ isolates of the ectomycorrhizal fungus Cenococcum geophilum associated with Populus trichocarpa soils in the Pacific Northwest, USA and comparison to globally distributed representatives

The ectomycorrhizal fungal symbiont Cenococcum geophilum is of high interest as it is globally distributed, associates with many plant species, and has resistance to multiple environmental stressors. C . geophilum is only known from asexual states but is often considered a cryptic species complex, since extreme phylogenetic divergence is often observed within nearly morphologically identical strains. Alternatively, C . geophilum may represent a highly diverse single species, which would suggest cryptic but frequent recombination. Here we describe a new isolate collection of 229 C . geophilum isolates from soils under Populus trichocarpa at 123 collection sites spanning a ~283 mile north-south transect in Western Washington and Oregon, USA (PNW). To further understanding of the phylogenetic relationships within C . geophilum , we performed maximum likelihood and Bayesian phylogenetic analyses to assess divergence within the PNW isolate collection, as well as a global phylogenetic analysis of 789 isolates with publicly available data from the United States, Japan, and European countries. Phylogenetic analyses of the PNW isolates revealed three distinct phylogenetic groups, with 15 clades that strongly resolved at >80% bootstrap support based on a GAPDH phylogeny and one clade segregating strongly in two principle component analyses. The abundance and representation of PNW isolate clades varied greatly across the North-South range, including a monophyletic group of isolates that spanned nearly the entire gradient at ~250 miles. A direct comparison between the GAPDH and ITS rRNA gene region phylogenies, combined with additional analyses revealed stark incongruence between the ITS and GAPDH gene regions, consistent with intra-species recombination between PNW isolates. In the global isolate collection phylogeny, 34 clades were strongly resolved using Maximum Likelihood and Bayesian approaches (at >80% MLBS and >0.90 BPP respectively), with some clades having intra- and intercontinental distributions. Together these data are highly suggestive of divergence within multiple cryptic species, however additional analyses such as higher resolution genotype-by-sequencing approaches are needed to distinguish potential species boundaries and the mode and tempo of recombination patterns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Characterizing juvenile salmon predation risk during early marine residence

Predation mortality can influence the distribution and abundance of fish populations. While predation is often assessed using direct observations of prey consumption, potential predation can be predicted from co-occurring predator and prey densities under varying environmental conditions. Juvenile Pacific salmon Oncorhynchus spp. (i.e., smolts) from the Columbia River Basin experience elevated mortality during the transition from estuarine to ocean habitat, but a thorough understanding of the role of predation remains incomplete. We used a Holling type II functional response to estimate smolt predation risk based on observations of piscivorous seabirds (sooty shearwater [ Ardenna griseus ] and common murre [ Uria aalge ]) and local densities of alternative prey fish including northern anchovy ( Engraulis mordax ) in Oregon and Washington coastal waters during May and June 2010–2012. We evaluated predation risk relative to the availability of alternative prey and physical factors including turbidity and Columbia River plume area, and compared risk to returns of adult salmon. Seabirds and smolts consistently co-occurred at sampling stations throughout most of the study area (mean = 0.79 ± 0.41, SD), indicating that juvenile salmon are regularly exposed to avian predators during early marine residence. Predation risk for juvenile coho ( Oncorhynchus kisutch ), yearling Chinook salmon ( O . tshawytscha ), and subyearling Chinook salmon was on average 70% lower when alternative prey were present. Predation risk was greater in turbid waters, and decreased as water clarity increased. Juvenile coho and yearling Chinook salmon predation risk was lower when river plume surface areas were greater than 15,000 km 2 , while the opposite was estimated for subyearling Chinook salmon. These results suggest that plume area, turbidity, and forage fish abundance near the mouth of the Columbia River, all of which are influenced by river discharge, are useful indicators of potential juvenile salmon mortality that could inform salmonid management.

Phillips, Elizabeth M. (ORCID:0000000327752563)↗
DOE OSTI2024

Forest carbon sequestration on the west coast, USA: Role of species, productivity, and stockability

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, “normal” stands without accounting for the substantial proportion of forests that don’t meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

Chisholm, Paul J. (ORCID:0000000238784707)↗
DOE OSTI2015

Newberry Well 55-29 Stimulation Data 2014

The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to run for weeks and deliver large volumes of water at moderate well-head pressure. Second, to stimulate multiple zones, AltaRock developed thermo-degradable zonal isolation materials (TZIMs) to seal off fractures in a geothermal well to stimulate secondary and tertiary fracture zones. The TZIMs degrade within weeks, resulting in an optimized injection/ production profile of the entire well. Third, the project followed a project-specific Induced Seismicity Mitigation Plan (ISMP) to evaluate, monitor for, and mitigate felt induced seismicity. An initial stimulation was conducted in 2012 and continued for 7 weeks, with over 41,000 m3 of water injected. Further analysis indicated a shallow casing leak and an unstable formation in the open hole. The well was repaired with a shallow casing tieback and perforated liner in the open hole and re-stimulated in 2014. The second stimulation started September 23rd, 2014 and continued for 3 weeks with over 9,500 m3 of water injected. The well was treated with several batches of newly tested TZIM diverter materials and a newly designed Diverter Injection Vessel Assembly (DIVA), which was the main modification to the original injection system design used in 2012. A second round of stimulation that included two perforation shots and additional batches of TZIM was conducted on November 11th, 2014 for 9 days with an additional 4,000 m3 of water injected. The stimulations resulted in a 3-4 fold increase in injectivity, and PTS data indicates partial blocking and creation of flow zones near the bottom of the well. This submission includes all of the files and reports associated with the stimulation, pressure testing, and monitoring included in the scope of the project.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

Newberry Volcano EGS Demonstration Well 55-29 Stimulation Data

The Newberry Volcano EGS Demonstration in central Oregon, a 3 year project started in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to run for weeks and deliver large volumes of water at moderate well-head pressure. Second, to stimulate multiple zones, AltaRock developed thermo-degradable zonal isolation materials (TZIMs) to seal off fractures in a geothermal well to stimulate secondary and tertiary fracture zones. The TZIMs degrade within weeks, resulting in an optimized injection/ production profile of the entire well. Third, the project followed a project-specific Induced Seismicity Mitigation Plan (ISMP) to evaluate, monitor for, and mitigate felt induced seismicity. Stimulation started October 17, 2012 and continued for 7 weeks, with over 41,000 m3 of water injected. Two TZIM treatments successfully shifted the depth of stimulation. Injectivity, DTS, and seismic analysis indicate that fracture permeability in well NWG 55-29 was enhanced by two orders of magnitude. This submission includes all of the files and reports associated with the geophysical exploration, stimulation, and monitoring included in the scope of the project.

15 GEOTHERMAL ENERGY↗