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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Kicking the can down the road: understanding the effects of delaying the deployment of stratospheric aerosol injection

Abstract Climate change is a prevalent threat, and it is unlikely that current mitigation efforts will be enough to avoid unwanted impacts. One potential option to reduce climate change impacts is the use of stratospheric aerosol injection (SAI). Even if SAI is ultimately deployed, it might be initiated only after some temperature target is exceeded. The consequences of such a delay are assessed herein. This study compares two cases, with the same target global mean temperature of ∼1.5° C above preindustrial, but start dates of 2035 or a ‘delayed’ start in 2045. We make use of simulations in the Community Earth System Model version 2 with the Whole Atmosphere Coupled Chemistry Model version 6 (CESM2-WACCM6), using SAI under the SSP2-4.5 emissions pathway. We find that delaying the start of deployment (relative to the target temperature) necessitates lower net radiative forcing (−30%) and thus larger sulfur dioxide injection rates (+20%), even after surface temperatures converge, to compensate for the extra energy absorbed by the Earth system. Southern hemisphere ozone is higher from 2035 to 2050 in the delayed start scenario, but converges to the same value later in the century. However, many of the surface climate differences between the 2035 and 2045 start simulations appear to be small during the 10–25 years following the delayed SAI start, although longer simulations would be needed to assess any longer-term impacts in this model. In addition, irreversibilities and tipping points that might be triggered during the period of increased warming may not be adequately represented in the model but could change this conclusion in the real world.

Brody, Ezra (ORCID:000900030008681X)↗
DOE OSTI2022

Ex-Situ Surface Characterization Studies and Boundary Plasma Diagnostic Development for DIII-D (Final Report)

This report details the accomplishments for award DE-SC0016318, which sponsored collaborative research activities between the University of Tennessee-Knoxville and the DIII-D experiment at General Atomics, led by the PI (Donovan), which officially began on August 1, 2016 and ended July 31, 2020. Though the official start date for the award was August 1, 2016, the PI had already initiated collaborative activities with DIII-D during 2015 supported by internal UTK start-up funds utilized by the PI. This prior work enabled UTK to have a substantial role in the June 2016 Metal Rings Campaign (MRC). The DOE funds then provided the opportunity to expand the UTK team with funding for students and a postdoc to perform ex-situ analysis on the wide array of samples exposed during the MRC and develop more sophisticated analysis tools and interpretive modeling techniques.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Label-based Virtual Directories In dCache

Traditional filesystems organize data in directories. These directories are typically a collection of files whose grouping is based on a single criterion, e.g., the starting date of an experiment, experiment name, beamline ID, measurement device, or instrument. However, each file in a directory can belong to several logical groups, such as a special event type, experiment condition, or a part of a selected dataset. dCache is a storage system developed to store large amounts of scientific data, used by many HEP and Photon Science experiments. With recent developments in dCache, we have introduced a concept of file tagging, which dynamically groups files with the same label into virtual directories. The file labels can be added, removed, renamed, and deleted through the admin interface or via REST API. The files in virtual directories are exposed through all protocols supported by dCache. This contribution will describe the details of the implementation for file tagging in dCache and present our future development plans on automatic metadata extractions, a feature that will significantly simplify data management. Additionally, we are exploring the future use of virtual directories as a way to translate scientific data catalogs into filesystem views for direct data analysis.

Sahakyan, Marina [DESY]↗
DOE OSTI2021

Application of sensitivity analysis in DYMOND/Dakota to fuel cycle transition scenarios

The ability to perform sensitivity analysis has been enabled for the nuclear fuel cycle simulator DYMOND through its coupling with the design and analysis toolkit Dakota. To test and demonstrate these new capabilities, a transition scenario and multi-parameter study were devised. The transition scenario represents a partial transition from the US nuclear fleet to a closed fuel cycle with small modular LWRs and fast reactors fueled by reprocessed used nuclear fuel. Four uncertain parameters in this transition were studied – start date of reprocessing, total reprocessing capacity, the nuclear energy demand growth, and the rate at which the fast reactors are deployed – with respect to their impact on four response metrics. The responses – total natural uranium consumed, maximum annual enrichment capacity required, total disposed mass, and total cost of the nuclear fuel cycle – were chosen based on measures known to be of interest in transition scenarios and to be significantly impacted by the varying parameters. Furthermore, analysis of this study was performed both from the direct sampling and through surrogate models developed in Dakota to calculate the global sensitivity measures Sobol’ indices. This example application of this new capability showed that the most consequential parameter to most metrics was the share of new build capacity that is fast reactors. However, for the cost metric, the scaling factor of the energy demand growth was significant and had synergistic behavior with the fast reactor new build share.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Systems Engineering and Analysis in Support of a US Federal Staging Facility for UNF

The US Department of Energy Office of Nuclear Energy (DOE-NE) Office of Spent Fuel and High-Level Waste Disposition is examining a set of system options and conducting supporting analyses to inform the development of an integrated waste management system, which may include one or more federal staging facilities (FSFs) for used nuclear fuel (UNF ) sited using a collaborative siting process. This paper focuses on the ongoing activities in two systems engineering and analysis work areas: (1) data and tools development, validation, and maintenance and (2) systems engineering execution. Within the first work area, the STANDARDS 5.0 UNF data and analysis tool, formerly known as UNF-ST&DARDS, is being developed as a foundational resource to assist in the management of UNF data. It has the key capability to model UNF throughout the entire back end of the fuel cycle. STANDARDS also includes several compatible analysis tools for the time-dependent characterization of UNF and related systems by interfacing with the SCALE code system for nuclear analysis and COBRA-SFS for thermal analysis. Also, within the data and tools area is the Next Generation System Analysis Model (NGSAM), which is an agent-based simulation software tool expressly designed to be capable of modeling the waste management system, including the transportation of UNF to and from a FSF. NGSAM has been developed to enable informed decision-making by providing the capability to analyze various potential system options for the management of UNF and high-level radioactive waste. Finally, in the systems engineering execution area, the team has begun to apply a disciplined systems engineering approach at the system level along with supporting analysis to guide the development of the FSF project requirements (including associated transportation infrastructure). Systems engineering principles and practices and their adaptation/application to design and development activities will ensure that the waste management system is effectively implemented as work proceeds. Other activities include investigating the implications of changes in various assumptions and parameters related to waste management systems, such as UNF acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed facility operation start dates. Keywords: federal staging facility (FSF), used nuclear fuel (UNF), integrated waste management (IWM) system, Next Generation System Analysis Model (NGSAM), STANDARDS, systems engineering

Joseph, Robert↗
DOE OSTI2021

CCF Parameter Estimations, 2020 Update

This report documents the quantitative results of the common-cause failure (CCF) data collection effort (which included data through 2020) and summarizes the results of the parameter estimation quantification process performed on CCF data in the U.S. Nuclear Regulatory Commission (NRC) CCF database. This is the 2020 update to NUREG/CR-5497, updating data and parameter estimations for CCFs. This release, CCF Parameter Estimation 2020, reflects the CCF data contained within the CCF database, https://rads.inl.gov/Pages/CCF.aspx, by executing (in August 2021) the CCF query rules in the folder SPAR Rules 2020. The data covers the period from 1/1/2006 to 12/31/2020, the most recent 15-year period in which data are available. The use of the most recent rolling 15-year data in parameter estimation differs from previous updates, in which 1/1/1997 was used as the starting date (e.g., 1/1/1997 to 12/31/2015 for the 2015 update, 1/1/1997 to 12/31/2012 for the 2012 update). The new date range (i.e., the most recent 15-year period), was selected for this CCF update so as to be consistent with the date range chosen for the component reliability parameter estimation, and with the effort to include sufficient data for analysis while simultaneously reflecting the most recent industry performance. These results are appropriate for use in probabilistic risk assessment (PRA) studies, including the Standardized Plant Analysis Risk (SPAR) models of commercial nuclear power plants (NPPs) in the U.S. This update may be referred as: U.S. Nuclear Regulatory Commission, "CCF Parameter Estimations, 2020 Update," https://nrcoe.inl.gov/publicdocs/CCF/ccfparamest2020.pdf, November 2021.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Flexible Siting Criteria and Staff Minimization for Micro-Reactors

The economic potential of micro-reactors is vast and underestimated. Commonly-emphasized applications include niche markets such as remote communities, mines and military bases. However, micro-reactors could be used as flexible energy generators also for larger markets, such as mobile and containerized agriculture and manufacturing facilities, district heating, micro-grids for data centers, sea ports, airports and hospitals. The implication is that micro-reactors may have to be deployed also in non-remote locations. Successful implementation of micro-reactors needs a navigable and predictable licensing process, technology-appropriate siting restrictions, risk-informed emergency and safety requirements, and practical operating and maintenance requirements. The primary goal of this project was to develop siting criteria that are tailored to micro-reactors deployable in densely-populated areas, e.g., urban environments. To achieve that goal, we compared the characteristics of the MIT research reactor (MITR) with those of leading micro-reactor concepts (e.g., eVinci, USNC, Aurora), and evaluated whether and how the MITR design basis (e.g., inherent safety features, engineered safety systems, source term, emergency planning and emergency operating procedures) and associated regulations may be applicable to these new micro-reactors as well. What makes MITR a unique analogue in this context is its small power rating (6 MWt) and physical size, mode of operations (24/7 with a somewhat more commercial flavor than typical university reactors), and especially its urban location. Of course significant differences exist, such as mission (power production vs. research) and the reactor design itself. Leveraging the MITR experience, this project was able to generate criteria that will allow micro-reactors to realize their full economic potential as flexible heat and electricity generators for a diverse portfolio of applications in non-remote locations. As such, the outcome of this project might encourage investment in and use of micro-reactors. A second goal of the project was to conceptualize a model of operations for micro-reactors that would minimize the staffing requirements, and thus reduce the cost of electricity and heat generated by these systems. Here too our approach was to systematically review the MITR experience and requirements, as well as survey the innovations in autonomous control technologies and monitoring (e.g., advanced sensors, drones, robotics, AI) that would permit a dramatic reduction in staffing at future micro-reactor installations. The scope of work was expanded after the start date to include also an evaluation of micro-reactor security, using the so-called consequence-based analysis, and the development of a methodology to perform dynamic risk assessment for micro-reactors, using system theory and modeling and simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

2D IR Microscopy—Technology for Visualizing Chemical Dynamics in Heterogeneous Environments (Final Technical Report)

The primary focus of this project was the design, prototype, and demonstration of a 2D IR microscope. The start date of this project was July 15, 2016 and the project end date was July 14, 2022. In the early years of this project our team designed, prototyped, and completely integrated a homebuilt microscope head with our high-repetition rate 2D IR spectrometer. Once in place our research team focused on characterizing the 2D IR microscope and using it to investigate model systems relevant to energy technologies. As part of this process, we identified two initial chemical systems to use to further develop 2D IR imaging modalities. The first chemical system developed was a room temperature ionic liquid (RTIL) electrolyte system and the second chemical system was a mixture of carbonates and salts developed as a battery electrolyte system. The completion of this project resulted in the full characterization of chemical dynamics in a bulk RTIL system and the demonstration of 2D IR imaging across the RTIL cast as a microdroplet in silicon oil. In addition, we explored the liquid structures and dynamics of organic carbonate mixtures from the vantage point of the vibrational probe, methyl thiocyanate. By the end of the project, we had moved toward in-depth studies of the organic carbonate mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine learning approaches for integrating multi-omics data to expand microbiome annotation

Preliminary: This final report corresponds to a grant (DE-SC0021216) that was awarded to the University of Montana. Mid-way through the grant period, I relocated from the University of Montana to the University of Arizona. The grant was ended at University of Montana in late 2022, with all efforts concluding on 08/26/22; the remaining funds supporting the project were relinquished by University of Montana, and were later awarded to University of Arizona under a new grant, with start date 04/01/23. This report focuses on results of research efforts at UMontana through 08/26/22. Results: We made progress in each of the three aims of the proposal. We released software that identifies and fills gaps in the annotation of metabolic proteins within bacterial genomes. We made substantial progress in developing software for alignment-based annotation of protein coding DNA, allowing for coding frameshifts caused by sequencing error. Finally, we made notable progress in developing AI methods (specifically: a neural embedding model) for identifying similarities between protein sequences based on amino-wise latent vectors. These efforts were supplemented by development of methods for protein modeling in support of predicting protein-drug binding activity, and by my leadership of a team in the NIH/DOE 2021 Petabyte-Scale Sequence Search hack-a-thon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Alaska Liquid Natural Gas Pipeline Front-End Engineering & Design (Final Technical Report)

The Alaska Gasline Development Corporation (AGDC) is Alaska’s natural gas infrastructure development corporation established in 2013. AGDC’s mission is to maximize the benefit of Alaska’s vast North Slope natural gas resources for Alaskans through the development of infrastructure necessary to move the gas into local and international markets. AGDC was identified for a Congressionally Directed Spending (CDS) project for funding in the Energy and Water Development and Related Agencies Appropriations Act, 2023 under the heading: “Congressionally Directed Energy Efficiency and Renewable Energy Projects.” The CDS included $\$$4,000,000 of direct funding, with required match funds, to move the project forward. Alaska’s North Slope holds America’s largest proven and conventional natural gas supply. The integrated Alaska LNG Project will deliver 3.5 billion cubic feet of natural gas per day from Alaska’s North Slope gas fields to Alaskans as well as to a marine terminal located at tidewater in Cook Inlet. Alaska LNG is an integrated gas infrastructure project with three major components: a gas treatment plant (GTP) located at Prudhoe Bay, an 807-mile (1,287 km) gas pipeline (Mainline Pipeline) to Southcentral Alaska with interconnections for in-state gas use, and a natural gas liquefaction facility (LNG Facility) in Nikiski, Alaska. The integrated Alaska LNG Project has several strategic advantages including proven gas resources, existing upstream infrastructure, an advantageous arctic climate for LNG production, proximity to LNG markets, a track record of reliability from a state that first began exporting LNG to Japan in 1969, and broad support from Alaskans. North Slope natural gas is a conventional resource and can be produced with minimal drilling at a fraction of the carbon dioxide emissions of shale gas from the Lower 48 states. Through the development of the Alaska LNG Project, Alaska can provide energy security to Alaskans and a stable source of LNG to the Asia-Pacific region for generations. The Alaska LNG Project has been progressed through Pre-Front-End Engineering Design (Pre-FEED) and has obtained all major federal and State of Alaska permits and authorizations to construct the project, including the Federal Energy Regulatory Commission (FERC) Order Granting Authorization Under Section 3 of the Natural Gas Act. On September 5, 2024, the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) awarded Project No. DE-FE0032307 to AGDC with the objective to progress the project to Front-End Engineering Design (FEED) entry for the Alaska LNG Project Phase 1 Pipeline. The award Start Date was made effective July 1, 2023, with a Period of Performance through June 30, 2025. On March 27, 2025, AGDC announced the execution of definitive commercial agreements with Glenfarne Alaska LNG, LLC, an affiliate of Glenfarne Group, LLC, (together as “Glenfarne”), to lead the development of the Alaska LNG Project and enter FEED for the Phase 1 Pipeline. Project activities are now funded and directed by this private sector partner who holds a 75% interest in 8 Star Alaska, LLC (8 Star). 8 Star holds the assets of the Alaska LNG Project. As planned, AGDC continues to hold 25% minority interest in 8 Star and will play a governance role moving forward with Alaska LNG. This definitive commercial agreement milestone led to the successful completion of AGDC’s Statement of Project Objectives (SOPO) for FEED entry and led to the completion of DOE Project No. DE-FE0032307. At conclusion of the SOPO, AGDC also reached the award’s maximum federal cost share of $\$$4,000,000. AGDC is, therefore, providing Final Technical Report to close out DOE Project No. DE-FE0032307.

02 PETROLEUM↗
DOE OSTI2025

Powernet in Farms Project

Coordinating behind-the-meter (BTM) distributed energy resources (DERs) is critical to ensuring efficiency and reliability for consumers facing an increasingly variable grid supply. Outside of very controlled environments, however, such coordination of heterogeneous resources at scale has remained a challenge due to harsh field conditions, the lack of adequate communication infrastructure, and the difficulty of modeling the system. The intent of this research was to refine the Powernet system deployed in a California dairy farm to achieve the following objectives: a) validate the results of the previous deployment and b) validate new hypothesis about system performance based on the simulation of the new system. The new system design would reduce the overall system cost, and achieve a payback period of less than 3 years, demonstrating the feasibility of such system and its relevance for a segment not well known for technology advancements in power systems. The new proposed system was significantly cheaper than the original design, which would enable the solution to be cost effective and likely economically viable. However, due to significant delays in project start date which affected funding availability, overlap with prior scheduled mandatory military leave from key members of the project team, and customer drop-out, due to the significant delays, which could not be replaced in time, caused the project to be ended prior to completion.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

How well are hazards associated with derechos reproduced in regional climate simulations?

Abstract. A 15-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of 29–30 June 2012 that impacted the northeastern urban corridor of the USA is presented. This event generated 1100 reports of damaging winds, generated significant wind gusts over an extensive area of up to 500 000 km2, caused several fatalities, and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global-warming experiments to examine the sensitivity of historical, societally important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic contexts. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as is manifest in high composite reflectivity, cREF), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBCs), start date, use of nudging, compiler choice, damping, and number of vertical levels). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g., convective available potential energy and vertical wind shear) and critical manifestations of deep convection, e.g., vertical velocities, cold-pool generation, and how those properties relate to the correct characterization of the associated atmospheric hazards (wind gusts and hail). Use of a double-moment, seven-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model-simulated wind gusts and convective structure to the observations of this event. All ensemble members, however, fail to capture the intensity of the event in terms of the spatial extent of convection and the production of high near-surface wind gusts. We further show very high sensitivity to the LBCs employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim compared to ERA5. Excess convective available potential energy (CAPE) in all ensemble members after the derecho passage leads to excess production of convective cells, wind gusts, cREF > 40 dBZ, and precipitation during a frontal passage on the subsequent day. This event proved very challenging to forecast in real time and to reproduce in the 15-member hindcast simulation ensemble presented here. Future work could examine if simulations with other initial and lateral boundary conditions can achieve greater fidelity.

Shepherd, Tristan (ORCID:0000000186276419)↗
DOE OSTI2023

NCSU Flux Tower Data

NCSU Flux Tower Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument descripotion Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Sonic Anemometer, 3 Condensation Particle Counters, 1 SP2, 1 POPS Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU flux tower was located next to the AMF sampling pad. The flux tower consisted of a 10 m telescoping tower. Mounted at the top of the tower was a sonic anemometer (RM Young 8000) and a Krypton Hygrometer. A sample line (¼” conductive tubing) and communication line was laid to a trailer located underneath and slightly adjacent to the tower. The sample line brought aerosol inside the trailer at 4.5 L min-1, where it was distributed between 3 CPCs (TSI 3776c, Dc ~ 2.5 nm, TSI 3771, Dc ~10nm, and TSI 3772, Dc ~40 nm) with different size cuts. Also sampling was a printed particle optical spectrometer (POPS) and a single particle soot photometer (SP2). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU RDMA data

NCSU RDMA Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Nano-Scanning Mobility Particle (SMPS); A Radial Differential Mobility Analyzer (RDMA) coupled with 1 Condensation Particle Counter Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU RDMA was operated at a sheath-to-sample flow ratio of 5:1.5 L min−1. The RDMA was configured to scan from 5 to 55 nm. It was located into the temperature-controlled trailer adjacent to the NCSU Flux Tower to observe size distributions of the aerosols.The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU HTDMA data

NCSU HTDMA data Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Humidified Tandem Differential Mobility Analyzer; 2 Differential Mobility Analyzers (DMA1 and DMA2). Start Date: 2022-06-01 End Date: 2022-09-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU HTDMA was operated at a sheath-to-sample flow ratio of 5:1 L min−1. The HTDMA was configured to measure hygroscopic growth factors of dry particles with mobility diameters of D = 15, 20, 30, 40, and 50 nm at RH ~ 70%. A complete cycle for all diameters took ~30 minutes. A sample line brought aerosol inside the trailer at 2.5 L min-1, where it was distributed between NCSU RDMA (1.5 L min-1) and NCSU HTDMA (1 L min-1) lines. The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. The sample line entered DMA1 (operated as an electrostatic classifier). Monodisperse particles with certain fractions were humidified with temperature controlled Nafion membrane immersed in water before entering DMA2 (operated in scanning mobility particle sizer). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU Black Carbon (SP2) Data

NCSU SP2 Data Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Single Particle Soot Photometer (SP2) Start Date: 2022-06-01 End Date: 2022-09-27 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The SP2 was located in the temperature-controlled trailer adjacent to the NCSU Flux Tower to observe refractory black carbon (rBC) number concentration and mixing states of black carbon. The sample line brought aerosol inside the trailer at 4.5 L min-1, where it was distributed between 3 CPCs (TSI 3776c, Dc ~ 2.5 nm, TSI 3771, Dc ~10nm, and TSI 3772, Dc ~40 nm) with different size cuts, a printed particle optical spectrometer (POPS), and SP2. Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Weather Data from BSEC Weather Stations

This dataset provides hourly measurements of temperature, humidity, rainfall, wind, and sunlight at Ambient Weather and OttHydro stations across Baltimore city. These surface weather stations were deployed by the Baltimore Social-Environmental Collaborative (BSEC) Urban Integrated Field Laboratory (UIFL) project, funded by the Department of Energy (DOE). This dataset will be periodically updated to include more stations and recent observations when available. Data File Information This dataset contains surface weather measurements data in comma-separated value (CSV) format and documents that describe the weather stations, locations, and measured parameters and units. data/BSEC-[STATIONID]_[SENSORTYPE]_hourly_[YEAR].csv Surface weather measurements data in CSV format, where STATIONID indicates the weather station, SENSORTYPE is the type of weather station ('AWS' = Ambient Weather Station and 'OTT' = 'OttHydro Station'), and YEAR indicate the year in which the measurements were made. Example data file name: BSEC-AAC_AWS_hourly_2023.csv. documents/Station_Locations.csv This CSV file provides location information and measurement start date for each surface weather station. documents/Weather_Station_Descriptions.pdf This document provides detailed description of the instruments along with their setup and accuracy of measurement. documents/File_Parameters.pdf This document describes the surface weather parameters and units of measurement.

Ambient Weather Stations↗