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At least 127 records · Page 7

U.S. Hydropower Market Report (January 2021 edition)

This is the third complete edition of the U.S. Hydropower Market Report (the first two were the 2014 and 2017 Hydropower Market Report published in 2015 and 2018, respectively). In intervening years between publishing the full report, updated data are also summarized and released, and can be found at the Oak Ridge National Lab (ORNL) HydroSource website. This report combines data from public and commercial sources as well as research findings from other Department of Energy (DOE) R&D projects in order to provide a comprehensive picture of developments in the U.S. hydropower and PSH fleet and industry trends. Prior to the first Market Report being published, there was a noted lack of publicly available and easily accessible information about hydropower in the United States and other important trends affecting this important sector of the energy industry. New and valuable types of information are constantly being developed in the course of DOE research activities and, in a rapidly evolving energy industry, it is important that these data be made available in a predictable and consistent manner for use by all different types of stakeholders and decision-makers.The report highlights developments in 2017–2019 (the years for which new data has become available since the publication of the 2017 Hydropower Market Report), and contextualizes this information compared to evolving high-level trends over the past 10–20 years. Apart from presenting trends over time, the report discusses differences in those trends by region, plant size, owner type, or other attributes.

13 HYDRO ENERGY↗

U.S. Hydropower Market Report

The January 2021 edition of the U.S. Hydropower Market Report is the third complete edition of this report (the first two were the 2014 and 2017 Hydropower Market Report published in 2015 and 2018, respectively). In intervening years between publishing the full report, updated data are also summarized and released, and can be found at the Oak Ridge National Lab (ORNL) HydroSource website. This report combines data from public and commercial sources, as well as research findings from other U.S. Department of Energy (DOE) R&D projects to provide a comprehensive picture of developments in the U.S. hydropower and pumped-storage hydropower fleet and industry trends. The report highlights developments in 2017–2019 (the years for which new data has become available since the publication of the 2017 Hydropower Market Report), and contextualizes this information compared to evolving high-level trends over the past 10–20 years. Apart from presenting trends over time, the report discusses differences in those trends by region, plant size, owner type, or other attributes.

13 HYDRO ENERGY↗

Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data obtained during calendar year (CY) 2019 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system, shown as Plant North. The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Background information in Section 2 of this report outlines the hydrogeologic framework for groundwater and surface water quality monitoring at Y-12 and includes an overview of the groundwater contamination in each hydrogeologic regime. Section 3 provides details regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP, including sampling locations and frequency, sample collection and handling, field measurements and laboratory analytes, quality assurance (QA)/quality control (QC) sampling, data management, and data quality assessment (DQA). However, the equivalent QA/QC or DQA information for the groundwater and surface water data associated with the monitoring programs implemented by UCOR are not included in this report and instead are deferred to referenced programmatic plans and reports issued by OREM and UCOR. Section 4 of this report presents a summary evaluation of the CY 2019 monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring. The evaluation is based primarily on the analytical results for the following principal groundwater contaminants at Y-12: nitrate, uranium, gross alpha activity, gross beta activity, and volatile organic compounds (VOCs). Section 5 summarizes the most significant findings with respect to the principal contaminants along with recommendations for any proposed changes to the ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP. Technical reports and plans cited in the narrative sections of the report are listed in Section 6. Narrative sections of this report reference several appendices. Figures (maps and diagrams) and data tables (excluding data summary tables incorporated in the narrative sections) are in Appendix A and Appendix B, respectively. Appendix C contains construction details for each well sampled during CY 2019 by either the Y-12 GWPP or UCOR, along with schematic diagrams for wells equipped with Westbay™ multiport sampling equipment or Barcad® pump systems. Appendix D supports the background summary discussion in Section 2 and provides more detailed information about the hydrogeologic framework for groundwater and surface water monitoring at Y-12, including the primary sources of groundwater contamination in each hydrogeologic regime. Results for all field measurements and laboratory analyses obtained by the Y-12 GWPP and UCOR are presented in Appendix E, which also includes the sample numbers for the QA/QC samples associated with groundwater and surface water monitoring performed by the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗

Software-defined Networking for Energy Delivery Systems (SDN4EDS): An Architectural Blueprint (Final Summary Report)

This is the initial version of a reference for suppliers and energy companies of all sizes to deploy networks based on software-defined networking technology (SDN) to improve reliability, reduce cyber security attack surface, and facilitate mitigation of adversarial behavior. It is a living document and will progress over the life cycle of the Software-Defined Networking for Energy Delivery Systems (SDN4EDS) project. Version 2 of this report provides information on the Red Team tabletop assessment performed against the initial reference architecture. Version 3 of this report updates the reference architecture with lessons learned from the Red Team tabletop assessment, as well as provides additional details for the use cases. It also provides information on the decision process that could be used by an organization when considering deploying SDN in their environment. The final version of this report consolidates all the interim reports generated by the project into a final report. It also draws from PNNL’s experience in deploying SDN to make recommendations on how SDN could be deployed in a utility environment, and provides rationale for those decisions allowing individual utilities to make risk-based and knowledge-based decisions on how to best deploy SDN in their own environment. This summary report provides a higher-level overview of the project reports. Readers interested in additional detail, including results of the Red Team assessments and the final configuration, are encouraged to read the full final report.

97 MATHEMATICS AND COMPUTING↗

Post-Closure Report for Closed Resource Conservation and Recovery Act Corrective Action Units, Nevada National Security Site, Nevada (CY2021)

This report serves as the combined annual report for post-closure activities in compliance with the requirements listed in Resource Conservation and Recovery Act (RCRA) Permit Number NEV HW0101 associated with the following closed corrective action units (CAUs): CAU 90, Area 2 Bitcutter Containment, CAU 91, Area 3 U-3fi Injection Well, CAU 92, Area 6 Decon Pond Facility, CAU 110, Area 3 WMD U-3ax/bl Crater, CAU 111, Area 5 WMD Retired Mixed Waste Pits, and CAU 112, Area 23 Hazardous Waste Trenches. This report covers calendar year 2021. The post-closure requirements for these sites are described in RCRA Permit NEV HW0101 and are summarized in each CAU-specific section of this report. The results of the inspections, a summary of maintenance activities, and an evaluation of monitoring data are presented in this report. This report will address all monitoring requirements noted in the RCRA Permit NEV HW0101, except groundwater monitoring. Groundwater monitoring is documented in the Nevada National Security Site Data Report: Groundwater Monitoring Program Area 5 Radioactive Waste Management Site. All required inspections, maintenance, and monitoring were conducted in accordance with the post-closure requirements of the permit. Revision 6 of RCRA Permit NEV HW0101 was issued effective December 10, 2015, and remained in effect until December 10, 2020. At the time of this report submittal, the new RCRA permit application was in review.

54 ENVIRONMENTAL SCIENCES↗

Ames National Laboratory Annual Site Environmental Report for CY2021

The primary purpose of this report is to summarize the performance of Ames National Laboratory’s environmental programs, present highlights of significant environmental activities, and confirm compliance with environmental regulations and requirements for calendar year 2021. This report is a working requirement of Department of Energy Order 231.1B, Environment, Safety and Health Reporting. It includes descriptions of the Laboratory’s site, mission, the status of its compliance with applicable environmental regulations, its planning and activities to maintain compliance, and a comprehensive review of its environmental protection, surveillance and monitoring activities. Ames National Laboratory is located on the campus of Iowa State University (ISU) and occupies 13 buildings owned by the Department of Energy (DOE). See the Laboratory’s Web page for location and Laboratory overview. The Laboratory also leases space in ISU owned buildings. In 2021, the Laboratory accumulated and disposed of hazardous waste under a U.S. Environmental Protection Agency (EPA) issued generator number. All waste was handled according to applicable EPA, State, and local regulations and DOE Orders. The Laboratory operates as a Small Quantity Generator (SQG) of hazardous waste. There were no radiological air emissions or exposures to the general public due to Laboratory activities in 2021 (See U.S. Department of Energy Air Emissions Annual Report in Appendix A.) The Laboratory has an established Environmental Radiological Protection Program (Plan 10200.041) per DOE Order 458.1 requirements. Plans, policies, and procedures are in place to protect the public and the environment against undue risk from radiation associated with DOE radiological activities. As indicated in prior Site Environmental Reports, formal pollution prevention awareness, waste minimization and recycling programs have been in practice since 1990, with improvements implemented most recently in 2017 with Iowa State University’s shift toward single-stream recycling. Included in recycling efforts are items such as batteries, monitors, corrugated cardboard, lamps, miscellaneous electronic office equipment, mixed paper, newsprint, food/beverage containers, and laboratory glassware. Ames National Laboratory also recycles/reuses salvageable metal, used oil, and foamed polystyrene peanuts, and encourages chemical redistribution and sharing among research groups. Ames National Laboratory reported its contractual performance to DOE-Ames Site Office (AMSO) through the Laboratory’s Performance Evaluation Measurement Plan (PEMP), and a performance level of “B+” was achieved in 2021 for Sustain Excellence and Enhance Effectiveness of Integrated Safety, Health, and Environmental Protection As reported in Site Environmental Reports for prior years, the Laboratory’s Environmental Management System (EMS) has been integrated into the Laboratory’s Integrated Safety Management System (ISMS) since 2005. The integration of EMS into Laboratory business practices allows the Laboratory to systematically review, address and respond to environmental impacts. In addition to DOE-identified objectives and targets, the EMS Steering Committee recommends annual environmental goals for the Laboratory. Due to the COVID-19 pandemic and limited onsite work staff, goals of reducing water usage and travel/commuting to promote the reduction of scope 3 greenhouse gases were achieved. All contract deliverables and environmental compliance activities were still met during this time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Post-Closure Report for Closed Resource Conservation and Recovery Act Corrective Action Units, Nevada National Security Site, Nevada: For Calendar Year 2020 (Rev. 2)

This report serves as the combined annual report for post-closure activities in compliance with the requirements listed in Resource Conservation and Recovery Act (RCRA) Permit Number NEV HW0101 associated with the following closed corrective action units (CAUs): 1) CAU 90, Area 2 Bitcutter Containment; 2) CAU 91, Area 3 U-3fi Injection Well; 3) CAU 92, Area 6 Decon Pond Facility; 4) CAU 110, Area 3 WMD U-3ax/bl Crater; 5) CAU 111, Area 5 WMD Retired Mixed Waste Pits; 6) CAU 112, Area 23 Hazardous Waste Trenches The locations of the sites are shown in Figure ES-1. This report covers calendar year 2020. The post-closure requirements for these sites are described in RCRA Permit NEV HW0101 and are summarized in each CAU-specific section of this report. The results of the inspections, a summary of maintenance activities, and an evaluation of monitoring data are presented in this report. Site inspections are conducted annually at CAUs 90, 91, and 112; semiannually at CAUs 92 and 110; and quarterly at CAU 111. Additional inspections are conducted at CAUs 92 and 111 if precipitation occurs in excess of 1.0 inch in a 24-hour period. Inspections include an evaluation of the condition of the units, including covers, fences, signs, gates, and locks. At CAUs 110 and 111, soil moisture monitoring and subsidence surveys are conducted in addition to the visual inspections. At CAU 110, the site fence, gate, lock, and use restriction signs are evaluated. At CAU 111, an ecological survey, direct radiation monitoring, air monitoring, radon flux monitoring, and groundwater monitoring are also conducted. This report will address all monitoring item notes above except groundwater monitoring. Groundwater monitoring is documented in the Nevada National Security Site Data Report: Groundwater Monitoring Program Area 5 Radioactive Waste Management Site. All required inspections, maintenance, and monitoring were conducted in accordance with the post-closure requirements of the permit. Revision 6 of RCRA Permit NEV HW0101 was issued effective December 10, 2015, and remained in effect until December 10, 2020. At the time of this report submittal, the new RCRA permit application was in review.

54 ENVIRONMENTAL SCIENCES↗

2022 Site Environmental Report: Idaho National Laboratory

The INL Site’s operations, as well as the ongoing cleanup mission involve a commitment to environmental stewardship and full compliance with environmental protection laws. As part of this commitment, the INL Site Environmental Report is prepared annually to inform the public, regulators, stakeholders, and other interested parties of the INL Site’s environmental performance during the year. This report is published for U.S. Department of Energy, Idaho Operations Office (DOE-ID) in compliance with DOE O 231.1B, “Environment, Safety and Health Reporting.” The purpose of the report is to provide the following: (1) Present the INL Site, mission, and programs, (2) Report compliance status with applicable federal, state, and local regulations, (3) Describe the INL Site environmental programs and activities, (4) Summarize results of environmental monitoring, (5) Discuss potential radiation doses to the public residing in the vicinity of the INL Site, (6) Report on ecological monitoring and research conducted by contractors and affiliated agencies and by independent researchers through the Idaho National Environmental Research Park, (7) Describe quality assurance methods used to ensure confidence in monitoring data, and (8) Provide supplemental technical data and reports that support the INL Site Environmental Report (https://idahoeser.inl.gov/publications.html).

54 ENVIRONMENTAL SCIENCES↗

Reported Energy and Cost Savings from the DOE ESPC IDIQ Program: FY 2024

Energy Savings Performance Contracts (ESPCs) are a contractual mechanism that allow a federal agency to procure energy savings and facility improvements without upfront capital costs to reduce costs and enhance mission resiliency. ESPCs are covered under FAR Part 23.2, and 42 USC § 8287. Section 8287(a)(2)(A) of Title 42 of the U.S. Code requires that each energy savings performance contract (ESPC) undergo an annual energy audit, resulting in a separate audit report for every project. The objective of the present report is to compile and analyze all annual ESPC audit reports issued between October 1, 2023, and September 30, 2024, for projects awarded under Generations 1, 2, and 3 of DOE’s ESPC IDIQ contracts. During this period, 205 measurement and verification (M&V) reports were produced for 200 projects; the total number of reports exceeds the number of projects because some projects generated more than one report (for example, a few projects measure savings twice per year and produce two audit reports annually, each covering a different six-month period). By aggregating the results from these individual audits, the report determines the portfolio-wide realization rate of energy and cost savings for all active ESPC projects awarded under DOE’s IDIQ program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quarterly Technical Progress Report Piperazine Advanced Stripper (PZAS™) Front End Engineering Design

EXECUTIVE SUMMARY This document summarizes the status of Cooperative Agreement DE-FE0031844, “Piperazine Advanced Stripper (PZAS™) Front-End Engineering Design,” during the reporting period of January 1 through March 31, 2020. The objective of this project is to develop accurate installed costs by conducting a Front-End Engineering Design (FEED) of PZAS™ at Golden Spread Electric Cooperative’s (GSEC) Mustang Station located in Denver City, TX. Complementary benefits include positioning the technology for a commercial project with the 45Q tax credits, qualifying PZAS™ for use on a Natural Gas Combined Cycle (NGCC) Cogen facility, and to provide cost detail to optimize PZAS™ and help guide R&D of second-generation solvent CO2 capture technologies. Results from the FEED will be used to evaluate the economic feasibility of the process at Mustang Station. This project is funded by the U.S. DOE National Energy Technology Laboratory under the aforementioned Cooperative Agreement. Exxon, Total, Chevron, UOP-Honeywell, and the University of Texas (UT) are project co-funders. AECOM and Trimeric are project team members; UT is the prime contractor. Summary of Progress Cooperative Agreement DE-FE0031844 was established in October 2019. The current reporting period, January 1 through March 31, 2020, is the second technical progress reporting period for the project. Several milestones were accomplished during this reporting period, including: • Kickoff Meeting with DOE on February 3, 2020. • Kickoff Meeting with GSEC on March 30, 2020. (Note: Due to Covid-19 travel restrictions and shelter-in-place guidelines, the kickoff meeting was conducted remotely via videoconferencing. See attached notes from that telecon.) • Updated Project Management Plan March 2020, submitted with this quarterly report Other activities during the quarter included progress on contracting and other legal agreements (e.g., non-disclosure agreements), internal kickoff meetings at both AECOM and Trimeric, and development of a Technical Implementation Plan (TIP). The TIP will help the team to make critical, early process decisions and, ultimately, to develop a project and process design basis. Note that all agreements between project team participants are complete as of this submittal, except the vendor agreement with Kiewit (steam cycle modeling). Plans for Next Reporting Period Activities during the next reporting period (April 1, 2020 through June 30, 2020) include: the completion of the Project Design Basis and progress towards the Process Design Basis/Process Design Package (PDP). The Project Design Basis is due as a deliverable and milestone during the next reporting period.

Rochelle, Gary T.↗

Submitting a Standard Compliance Annual Report: EPAct State and Alternative Fuel Provider Fleet Program User Guide

State government and alternative fuel provider fleets covered under the State and Alternative Fuel Provider Fleet Program (Program) established pursuant to the Energy Policy Act of 1992 (EPAct) may use the Compliance Reporting Tool to track and report on several compliance activities. These activities include, but are not limited to, completing Standard Compliance annual reports, Alternative Compliance notices of intent, and exemption requests. Covered fleets can access the Compliance Tool through the Program's website at https://epact.energy.gov/users/sign_in. Covered fleet points of contact should bookmark the Compliance Reporting Tool for future access. This user guide addresses how to complete and submit Standard Compliance annual reports, including getting started with reporting, submitting annual reports, submitting exemption requests, and viewing annual reports.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of Strong Anaerobic Fluorescent Reporters for Clostridium acetobutylicum and Clostridium ljungdahlii Using HaloTag and SNAP-tag Proteins

One of the biggest limitations in the study and engineering of anaerobic Clostridium organisms is the lack of strong fluorescent reporters capable of strong and real-time fluorescence. Recently, we developed a strong fluorescent reporter system for Clostridium organisms based on the FAST protein. Here, we report the development of two new strong fluorescent reporter systems for Clostridium organisms based on the HaloTag and SNAP-tag proteins, which produce strong fluorescent signals when covalently bound to fluorogenic ligands. These new fluorescent reporters are orthogonal to the FAST ligands and to each other, allowing for simultaneous labeling and visualization. We used HaloTag and SNAP-tag to label the strictly anaerobic organisms Clostridium acetobutylicum and Clostridium ljungdahlii. We have also identified a new strong promoter for protein expression in C. acetobutylicum, based on the phosphotransacetylase gene (pta) from C. ljungdahlii. Furthermore, the HaloTag and the SNAP-tag, in combination with the previously described FAST system, were successfully used to measure cell populations in bacterial mixed cultures and showed the simultaneous orthogonal labeling of HaloTag and SNAP-tag together with the FAST protein reporter. Finally, we show the expression of recombinant fusion protein of FAST and the ZapA division protein (from C. acetobutylicum) in C. ljungdahlii. The availability of multiple strong fluorescent reporters is a major addition to the genetic toolkit of Here, Clostridium and other anaerobes that will lead to better understanding of these unique organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Prevalence of Self-Reported Voice Concerns and Associated Risk Markers in a Nonclinical Sample of Military Service Members

Introduction: Difficult communication environments are common in military settings, and effective voice use can be critical to mission success. This study aimed to estimate the prevalence of self-reported voice disorders among U.S. military service members and to identify factors that contribute to their voice concerns. Method: A nonclinical sample of 4,123 active-duty service members was recruited across Department of Defense hearing conservation clinics. During their required annual hearing evaluation, volunteers provided responses to voice-related questions including a slightly adapted version of the Voice Handicap Index-10 (VHI-10) as part of a larger survey about communication issues. Changepoint detection was applied to age and years of service to explore cohort effects in the reporting of voice concerns. Logistic regression analyses examined multiple available factors related to communication to identify factors associated with abnormal results on the VHI-10. Results: Among the respondents, 41% reported experiencing vocal hoarseness or fatigue at least several times per year, and 8.2% ( n = 336) scored above the recommended abnormal cut-point value of 11 on the VHI-10. Factors independently associated with the greatest risk for self-reported voice concerns were sex (female), cadmium exposure, vocal demands (the need for a strong, clear voice), and auditory health measures (frequency of experiencing temporary threshold shifts; self-reported hearing difficulties). Conclusions: Based on self-reported voice concerns and false negative rates reported in the literature, the prevalence of dysphonia in a large sample of active-duty service members is estimated to be 11.7%, which is higher than that in the general population. Certain predictors for voice concerns were expected based on previous literature, like female sex and voice use, but frequency of temporary threshold shifts and exposure to cadmium were surprising. The strong link between voice and auditory problems has particular implications regarding the need for effective communication in high-noise military and other occupational environments.

Audiology & Speech-Language Pathology↗

Large-scale deep learning for metastasis detection in pathology reports

Objectives No existing algorithm can reliably identify metastasis from pathology reports across multiple cancer types and the entire US population. In this study, we develop a deep learning model that automatically detects patients with metastatic cancer by using pathology reports from many laboratories and of multiple cancer types. Materials and Methods We use 60 471 unstructured pathology reports from 4 Surveillance, Epidemiology, and End Results (SEER) registries. The reports were coded into 1 of 3 labels: metastasis negative, metastases positive, or metastasis undetermined. We utilize a task-specific deep neural network trained from scratch and compare its performance with a widely used large language model (LLM). Results Our deep learning architecture trained on task-specific data outperforms a general-purpose LLM, with a recall of 0.894 compared to 0.824. We quantified model uncertainty and used it to defer reports for human review. We found that retaining 72.9% of reports increased recall from 0.894 to 0.969. Discussion A smaller deep learning architecture trained on task-specific data outperforms a general LLM. Equally critical to model performance is the incorporation of uncertainty quantification, achieved here through an abstention mechanism. Conclusions This study’s finding demonstrate the feasibility of developing algorithms to automatically identify metastatic cancer cases from unstructured pathology reports.

machine learning↗

Using case-level context to classify cancer pathology reports

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence—for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We test our approach on a corpus of 431,433 cancer pathology reports, and we show that incorporating case-level context significantly boosts classification accuracy across six classification tasks—site, subsite, laterality, histology, behavior, and grade. We expect that with minimal modifications, our add-on can be applied towards a wide range of other clinical text-based tasks.

60 APPLIED LIFE SCIENCES↗

Data from: “Enabling FAIR data in Earth and environmental science with community-centric (meta)data reporting formats”

This dataset contains supplementary information for a manuscript describing the ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) data repository's community data and metadata reporting formats. The purpose of creating the ESS-DIVE reporting formats was to provide guidelines for formatting some of the diverse data types that can be found in the ESS-DIVE repository. The 6 teams of community partners who developed the reporting formats included scientists and engineers from across the Department of Energy National Lab network. Additionally, during the development process, 247 individuals representing 128 institutions provided input on the formats. The primary files in this dataset are 10 data and metadata crosswalk for ESS-DIVE’s reporting formats (all files ending in _crosswalk.csv). The crosswalks compare elements used in each of the reporting formats to other related standards and data resources (e.g., repositories, datasets, data systems). This dataset also contains additional files recommended by ESS-DIVE’s file-level metadata reporting format. Each data file has an associated dictionary (files ending in _dd.csv) which provide a brief description of each standard or data resource consulted in the data reporting format development process. The flmd.csv file describes each file contained within the dataset.

54 ENVIRONMENTAL SCIENCES↗

Crowdsourcing Felt Reports Using the MyShake Smartphone App

MyShake is a free citizen science smartphone app that provides a range of features related to earthquakes. Features available globally include rapid postearthquake notifications, live maps of earthquake damage as reported by MyShake users, safety tips, and various educational features. The app also uses the accelerometer in the mobile device to detect earthquake shaking, and to record and submit waveforms to a central archive. In addition, MyShake delivers earthquake early warning alerts in California, Oregon, and Washington. Here, in this study, we compare the felt shaking reports provided by MyShake users in California with the U.S. Geological Survey’s (USGSs) “Did You Feel It?” intensity reports. The MyShake app simply asks, “What strength of shaking did you feel?” and users report on a five-level scale. When the MyShake reports are averaged in spatial or time bins, we find strong correlation with the Modified Mercalli Intensity scale values reported by the USGS based on the DYFI surveys. The MyShake felt reports can therefore contribute to the creation of shaking intensity maps.

58 GEOSCIENCES↗

Herbaceous Feedstock 2018 State of Technology Report

The U.S. Department of Energy (DOE) promotes the production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement with this mission, Idaho National Laboratory (INL) completes an annual SOT report for biomass feedstock logistics. This report summarizes supply system impacts of Bioenergy Technologies Office (BETO)-funded research and development efforts at INL and elsewhere (such as the High-Tonnage Feedstock Logistics projects (Webb et al. 2013a, Webb et al. 2013b, Webb et al. 2013c, Webb and Sokhansanj 2014, Sokhansanj et al. 2014) that lead to improvements in feedstock supply systems. These include improvements to and observed performance of innovative harvest and collection methods, storage technologies, transportation and handling approaches, and advanced preprocessing technologies. Biomass quality and variability, and the interface between feedstock quality and conversion performance are key drivers in addition to delivered feedstock cost. In this report, we estimate the benefits of R&D improvements to individual supply system unit operations, and present the status of feedstock logistics technology development for converting biomass into biofuels. These analyses are supported by experimental data where possible, and help to align the SOT relative to the cost goals defined in the Multi-Year Program Plan. The 2018 Herbaceous SOT aligned feedstock logistic design with current biorefinery’s design capacity utilized by biochemical conversion platform. Currently biochemical conversion platform utilizes a 725,000 dry ton/year biorefiney design for the techno economic analysis. Hence, feedstock delivered cost in the 2018 Herbaceous SOT is calculated based on biorefinery’s 725,000 dry ton design capacity instead of 800, 000 dry ton capacity utilized in the 2017 Herbaceous SOT. Biomass availabilities in this SOT were updated to year 2018 data from the 2016 Billion-Ton Report (BT16) (DOE 2016a), with the exception of switchgrass, for which the 2018 Herbaceous SOT utilized the 2019 switchgrass availability data from BT16. The BT16 report (DOE 2016a) does not project switchgrass availability in 2018; the soonest switchgrass is available in the BT16 report is 2019. Therefore, availability of switchgrass for this analysis was that projected for 2019. The 2018 Herbaceous SOT incorporates same technologies utilized in the 2017 Herbaceous SOT. However, a sensitivity analysis is performed to understand the impact of variation of process parameters on those technologies on feedstock logistic cost. New R&D data that shows the variations of process parameters affecting process performance is incorporated in the 2018 SOT to measure the variations in delivered feedstock cost. The 2018 Herbaceous SOT has also provided projected delivered feedstock of 2022 design case based on near term technical target under BETO funded R&D project. Finally, updated biorefinery size of 725,000 dry ton/year was incorporated within least-cost formulation model to select optimal siting and depot scales during optimization of the least cost blend. This modification to the optimization algorithm allows the trade-off between the cost of increased supply radius and the savings from selecting biomass from higher producing counties to be assessed. Such optimization has also showed the economic benefit of decentralized depots in comparison to centralized preprocessing co-located with the biorefinery by decoupling the biorefinery and feedstock locations. The 2018 Herbaceous SOT report documents the current modeled cost of a herbaceous feedstock supply system (from harvest to the pretreatment reactor throat, including grower payment) for hydrocarbon fuel production via biochemical conversion, based on equipment and processes now available or potentially available in the near term. The modeled cost also considers both the required quality and the availability of the biomass resources. The 2018 Herbaceous SOT predicts a modeled delivered feedstock cost of $83.67/dry ton (2016$); this is a $0.23/dry ton (2016$) decrease from the 2017 Herbaceous SOT. The modification of biorefinery’s designed capacity and increased projected biomass availability in the same supply shed contributed to this modeled cost reduction. The least-cost formulation model to optimally site and scale local distributed preprocessing depots also contributed to the cost reduction by considering county-level grower payment and distance from the biorefinery as variables in the optimization algorithm. Sensitivity analysis on various process parameters that affect delivered feedstock cost in the 2018 Herbaceous SOT shows that the delivered cost could varies from $80.45-$88.83/dry ton. The top factors that causes such variations are: effective baling rate, bale density, hammer mill throughput, interest rate and storage dry matter loss.

09 BIOMASS FUELS↗