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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A multi-ancestry genetic study of pain intensity in 598,339 veterans

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25–50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, β-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Meeting the Challenges of Modern Transit through the Integration of Traditional Transit, On-Demand Micro-Transit Services and Vehicle Automation - A Case Study in Chandler, Arizona

Current technology trends of vehicle automation, electrification and on-demand transit are providing new tools to develop effective public mobility services, yet need to be balanced with traditional modes to serve the spectrum of demand effectively and efficiently. Automated vehicle transportation network company (TNC) services, better known as 'Robotaxis' are beginning to proliferate and scale across the US, with Waymo as the lead commercial entity. Chandler, AZ was the first fully automated deployment of Waymo technology. Chandler was also one of the first municipalities in Arizona to roll out micro-transit service to its citizens in 2022. At present the Chandler Flex micro-transit program is beginning to partner with Waymo to augment micro-transit services during peak demands, another first in the nation. However, the mix of services in Chandler relies not only on new technology, but also on traditional modes including fixed route transit and para-transit services. These are blended and balanced such that both old and new modes are applied within the context in which each excel. This presentation will provide background on the Chandler, AZ public mobility services, and the performance metrics that govern their use and selection within the spectrum of development and population density as well as socio-demographics within Chandler. Additionally, the behavioral response of the use of unmanned, automated vehicles employed to augment micro-transit is novel, the first in the nation - and initial feedback from public transit constituents in Chandler will be shared.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Combined Techno-Economic Analysis and Life Cycle Assessment of an Integrated Direct Air Capture System with Advanced Algal Biofuel Production

The continuous increase in carbon dioxide (CO2) concentration in the atmosphere since the First Industrial Revolution correlates convincingly with the ongoing rise of the Earth's global average temperature contributing to climate change. As a response, carbon capture and sequestration (CCS) technologies are being implemented to mitigate anthropogenic CO2 emissions by capturing CO2 from high emitting point sources, such as power plants, refineries, and cement factories, and subsequently buried in geological formations underground for long term storage. Recently direct air capture (DAC) has emerged as a promising alternative technology that captures CO2 directly from the atmosphere for use or sequestration. This study investigates the potential synergistic benefits of integrating a solid amine-based DAC system with advanced algal biofuel production in photobioreactors (PBRs). DAC utilization allows the removal of atmospheric CO2 while also decoupling algae production facilities from anthropogenic point CO2 sources and avoiding the cost and logistics challenges of transporting CO2 long distances to remote facilities. Techno-economic analysis and life cycle assessment are performed to assess the economic and environmental benefits of heat and mass integration between the DAC and the PBR for biofuel production. The DAC-PBR system integration also considers on-site flue gas handling options, DAC capital utilization, the tradeoff between centralization or decentralization of key unit operations, and the PBR array. This presentation will discuss how optimizing DAC-PBR process integration can enhance the algal biofuel's economic and environmental sustainability and the prospect of DAC enabling the circular carbon economy.

algal biofuel production↗
DOE OSTI2022

Correlative SIP-FISH-Raman-SEM-NanoSIMS links identity, morphology, biochemistry, and physiology of environmental microbes

Microscopic and spectroscopic techniques are commonly applied to study microbial cells but are typically used on separate samples, resulting in population-level datasets that are integrated across different cells with little spatial resolution. To address this shortcoming, we developed a workflow that correlates several microscopic and spectroscopic techniques to generate an in depth analysis of individual cells. By combining stable isotope probing (SIP), fluorescence in situ hybridization (FISH), scanning electron microscopy (SEM), confocal Raman microspectroscopy (Raman), and nano-scale secondary ion mass spectrometry (NanoSIMS), we illustrate how individual cells can be thoroughly interrogated to obtain information about their taxonomic identity, structure, physiology, and metabolic activity. Analysis of an artificial community demonstrated that our correlative approach was able to resolve the activity of single cells using heavy water SIP in conjunction with Raman and/or NanoSIMS and establish their taxonomy and morphology using FISH and SEM. We then applied this workflow to a sample of yet uncultured multicellular magnetotactic bacteria. In addition to establishing their identity and activity, backscatter electron microscopy (BSE), NanoSIMS, and energy-dispersive X-ray spectroscopy (EDS) were employed to characterize the magnetosomes within the cells. By integrating these techniques, we demonstrate a cohesive approach to thoroughly study environmental microbes at single cell resolution.

Schaible, George↗
DOE OSTI2023

Techno-Economic Analysis of Dynamic Building Envelopes Comprising Phase Change Materials and Switchable Insulations: Preprint

Integrating phase change materials (PCMs) in building envelopes is a recognized technique to reduce the space heating/cooling loads and provide load shedding and shifting capacity. However, PCM benefits have been found to reduce dramatically with increase in the insulation requirements. Dynamic building envelopes that can alter their thermal resistance based on the indoor and outdoor conditions can effectively harness free ambient heating/cooling, thereby greatly enhancing the benefits of the PCM-integrated envelope in managing thermal loads. In this study, we examine various combinations of PCMs and switchable insulations and compare their combined impact on heat flow through the building envelope. Using numerical analysis, we investigate the PCM- and switchable insulation-integrated building walls, calculate the potential energy saving benefits compared to the conventional static walls, and finally perform technoeconomic analysis to estimate the acceptable cost of the technology under various payback period scenarios.

dynamic building envelopes↗
DOE OSTI2022

Techno-Economic Analysis of Dynamic Building Envelopes Comprising Phase Change Materials and Switchable Insulations

Integrating phase change materials (PCMs) in building envelopes is a recognized technique to reduce the space heating/cooling loads and provide load shedding and shifting capacity. However, PCM benefits have been found to reduce dramatically with increase in the insulation requirements. Dynamic building envelopes that can alter their thermal resistance based on the indoor and outdoor conditions can effectively harness free ambient heating/cooling, thereby greatly enhancing the benefits of the PCM-integrated envelope in managing thermal loads. In this study, we examine various combinations of PCMs and switchable insulations and compare their combined impact on heat flow through the building envelope. Using numerical analysis, we investigate the PCM- and switchable insulation-integrated building walls, calculate the potential energy saving benefits compared to the conventional static walls, and finally perform techno-economic analysis to estimate the acceptable cost of the technology under various payback period scenarios.

dynamic building envelopes↗
DOE OSTI2024

Grid Integration of Renewable Energy and Energy Storage

Grid integration of renewable energy and energy storage requires forward-looking planning process, and increased emphasizes on reliability, resilience, and equity. Power-electronics based energy generation including solar, wind, distributed energy resources (DERs), and various types of grid-tied energy storage and emerging loads, are reshaping grid operator's understanding on interconnection level performance and responses. This paper will present the ongoing work at PNNL related to power electronics R&D, energy modeling and analysis, and a wide spectrum of grid stability studies and technologies in support of grid integration of renewable energy and energy storage.

Power Electronics, grid integration of renewable e↗
DOE OSTI2024

Modeling and Assessment of Integrated Hydroelectric Power and Hydrogen Energy Storage

Environmental and regulatory constraints are increasingly posing challenges to the optimal operation of hydroelectric facilities. Hydrogen energy storage (HES) is well-suited to address these challenges.Using excess or low-cost hydroelectric power during off-peak hours to produce hydrogen can help reduce water spills and unlock opportunities for energy arbitrage. Moreover, the oxygen byproduct of electrolysis can be used to improve the dissolved oxygen (DO) levels in tailrace water. %, a key water quality metric for hydroelectric facilities.This paper presents an innovative framework for modeling and assessing the integrated hydroelectric-hydrogen system, considering subsystem constraints and coupling, benefits in spill water reduction and DO mitigation, as well as diverse hydrogen utilization, including re-electrification, blending with natural gas, and direct sales. Comprehensive case studies were conducted to assess the techno-economic performance of the integrated system in different deployment scenarios.

Energy storage, Hydrogen, Hydropower, Optimization↗
DOE OSTI2025

Capacity Design Method for Integrated Convective/Radiant Terminals to Guarantee Overall and Local Environment

To achieve energy efficiency in the operation of heating devices and ensure thermal comfort in indoor environments, the integrated convective/radiant terminals have become an important development direction for heating systems. This study selected a 14 m 2 bedroom hot summer and cold winter region in China as a case study. Computational Fluid Dynamics (CFD) methodology was used to investigate the design of integrated convective/radiant terminals to ensure thermal comfort for both the entire room and partial space. The results indicate that focusing on partial space during the steady-state stage can achieve energy savings of 31.1% compared to guaranteeing the entire room. Additionally, during the start-up stage, there is a significant reduction of convective unit capacity by 17.6% when the start-up time is 15 minutes. These findings provide data support for the design and engineering applications of products of integrated convective/radiant terminals. Besides, the excess convection ratios for the entire room and partial space are specified as 0.69 to 0.80 and 0.73 to 0.83, respectively.

Chi, Junjie↗
DOE OSTI2025

Evaluating Thermostats' Deadbands Using HVAC Hardware-In-the-Loop Experiment for Advanced Control Strategies

Smart thermostats have gained significant popularity due to their potential for optimizing energy consumption and enhanced user control while ensuring occupants' comfort. The deadband, also referred to as temperature differential, is defined as the temperature difference between the desired setpoint and upper threshold or lower threshold for the HVAC equipment to turn on. It is a key factor influencing energy efficiency and user satisfaction. This paper presents a comparative analysis of the deadbands of five different smart thermostats, tested with a heat pump, aiming to identify variations in their deadband settings and implications for energy management. The experimental study was conducted using a HVAC hardware-in-theloop (HIL) system that integrates smart thermostats with physical HVAC equipment in a simulated house environment. The study explores the trade-offs between energy efficiency and occupant comfort and highlights how different thermostats participating in demand response event cycle differently based on their deadband settings. The findings offer valuable insights into how selecting the right thermostat or configuring smart thermostat with appropriate deadband settings can be leveraged to enhance demand response capabilities, shift loads effectively and improve operational flexibility in HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Evaluating Thermostats' Deadbands Using HVAC Hardware-In-the-Loop Experiment for Advanced Control Strategies: Preprint

Smart thermostats have gained significant popularity due to their potential for optimizing energy consumption and enhanced user control while ensuring occupants' comfort. The deadband, also referred to as temperature differential, is defined as the temperature difference between the desired setpoint and upper threshold or lower threshold for the HVAC equipment to turn on. It is a key factor influencing energy efficiency and user satisfaction. This paper presents a comparative analysis of the deadbands of five different smart thermostats, tested with a heat pump, aiming to identify variations in their deadband settings and implications for energy management. The experimental study was conducted using a HVAC hardware-in-theloop (HIL) system that integrates smart thermostats with physical HVAC equipment in a simulated house environment. The study explores the trade-offs between energy efficiency and occupant comfort and highlights how different thermostats participating in demand response event cycle differently based on their deadband settings. The findings offer valuable insights into how selecting the right thermostat or configuring smart thermostat with appropriate deadband settings can be leveraged to enhance demand response capabilities, shift loads effectively and improve operational flexibility in HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Part-scale microstructure prediction for laser powder bed fusion Ti-6Al-4V using a hybrid mechanistic and machine learning model

Laser powder bed fusion (LPBF) Ti-6Al-4V is widely studied for use in structural applications in aerospace and medical industries, but mechanical anisotropy and microstructural inhomogeneity prohibits its wider adoption. Although successful microstructure prediction models have been developed, a remaining challenge is their limited integration across length/time scales and validation by experimental studies. Here, this work proposes a physics-augmented machine learning surrogate model to unite predictions of LPBF temperature, β phase morphology and texture, and α/α’ formation into a single framework that is calibrated and validated with experiments. First, a phase field (PF) model of the martensitic β→α’ transformation is developed and calibrated using data from in-situ synchrotron cyclic heating/cooling studies quantifying the variation of α phase fraction with time. In parallel, an established finite difference-Monte Carlo (FDMC) model predicts the part-scale temperature profile and β grain formation during solidification. A dataset is developed using LPBF cyclic temperature descriptors from the FDMC model as inputs and corresponding α/α’ phase fraction and width from the PF model as outputs. Five machine learning (ML) regression models are tested and optimized, having mean absolute error in testing ≤ 4 %, and the k-nearest neighbors (KNN) model is selected as the best performing. The KNN model is called at the nodal level during post-processing of the FDMC model to replace and downscale the response of the PF model. The combined agility and accuracy of the hybrid FDMC-ML model enables part-scale microstructure predictions that can be further used for property predictions to accelerate AM process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Faraday detector uranium isotope ratio measurement: Insights from solution- and laser ablation-based sampling methodologies on the Neoma MC-ICP-MS

In this study we utilize an all-faraday cup detector configuration on the Neoma MC-ICP-MS to perform uranium isotope ratio determinations from certified reference materials and a nuclear fuel precursor material via solution and laser ablation based sampling methodologies. The goal in performing these measurements is primarily to demonstrate that the all-faraday cup method can produce highly precise and accurate isotope ratios even at relatively low signal intensity levels while also developing a preliminary understanding of how the complex interplay between different amplifier resistor levels (e.g. 10 11 vs 10 13 Ω) and integration times impacts the precision and accuracy of different types of measurements. Our results show that the faraday cups with 1013 Ω resistors in their amplifier feedback loops can be used to produce accurate and relatively precise isotope ratios for ion beams down to ~5 K cps. However, at the lower end of the signal intensities observed in this study, longer integration times are necessary to mitigate the impact of ion beam instability that can occur during laser ablation based sampling. Despite this potential limitation, the all-faraday cup method is highly versatile as exemplified by the analysis of a collection of uranium reference materials with highly variable uranium isotopic compositions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Framework to Integrate Human Reliability Data Obtained from Different Sources Based on the Complexity Scores of Proceduralized Tasks

For many decades, PSA (Probabilistic Safety Assessment) or PRA (Probabilistic Risk Assessment) techniques have been used to enhance the operational safety of nuclear power plants (NPPs) based on the consideration of potential hazards that could result in an unexpected consequence. As human error is one of the potential hazards, diverse human reliability analysis (HRA) methods have been proposed to provide a systematic way to estimate the likelihood of human errors (i.e., human error probability, HEP) in specific task contexts. Accordingly, it is evident that the quality of HRA results strongly depends on the credibility of HEP estimations. This implies that, in terms of enhancing this credibility, the collection of raw information (HRA data) that is helpful for understating when and why human errors occur is a crucial issue. In order to address this issue, in this study, the feasibility of a framework to integrate HRA data obtained from different sources is investigated based on the complexity of proceduralized tasks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

A superconducting quantum simulator based on a photonic-bandgap metamaterial

Synthesizing many-body quantum systems with various ranges of interactions facilitates the study of quantum chaotic dynamics. Such extended interaction range can be enabled by using nonlocal degrees of freedom such as photonic modes in an otherwise locally connected structure. Here, we present a superconducting quantum simulator in which qubits are connected through an extensible photonic-bandgap metamaterial, thus realizing a one-dimensional Bose-Hubbard model with tunable hopping range and on-site interaction. Using individual site control and readout, we characterize the statistics of measurement outcomes from many-body quench dynamics, which enables in situ Hamiltonian learning. Further, the outcome statistics reveal the effect of increased hopping range, showing the predicted crossover from integrability to ergodicity. Our work enables the study of emergent randomness from chaotic many-body evolution and, more broadly, expands the accessible Hamiltonians for quantum simulation using superconducting circuits.

Science & Technology - Other Topics↗
DOE OSTI2024

EPCAPE-PT-LANL Measurements: Wideband Integrated Bioaerosol Sensor

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Wideband Integrated Bioaerosol Sensor (Droplet Measurements Technology) Data Notes: The WIBS is an online single-particle measurement that detects FBAPs (within a size range of 0.5 - 30 microns in diameter) based on the excitation and emission wavelengths of the individual particles. Using two xenon lamps, the WIBS excites FBAPs at 280 nm and 370 nm. Their emission is detected across two wavebands of 310-400 nm and 420-650 nm. We classified the FBAPs into seven different categories (A, B, C, AB, BC, AC, and ABC) using the classification scheme in Perring et. al. (2015) [1]. Averaged number concentration of FBAPs (total and by category) and particles that non-fluorescent bioaerosols particles (NFBAPs). In separate files, we also present one-minute-averaged size distributions and the asymmetry factor (AF, a surrogate for shape) of all FBAPs and NFBAPs. The logarithmic bin width of the size bins are the same as the average bin width of the AOS's optical particle counter (OPC, Grimm) for the range of sizes in which they overlap (26 bins from 0.5 - 30 microns). AF of the particles ranges from 0-100 and is divided into five bins with a linear spacing at increments of 20. The smallest AF bin represents more spherical particles while the largest bin represents more rod-shaped particles. [1] Perring, A. E., et al. (2015), Airborne observations of regional variation in fluorescent aerosol across the United States, J. Geophys. Res. Atmos., 120, 1153–1170, doi:10.1002/2014JD022495. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2023epcape-pt-lanl. Files data_10min_WIBS_AFDist.csv Header: - FBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of FBAPs detected during the measurement. - NFBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of non-fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of NFBAPs detected during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. AF Bins: • Bin 1: 0 – 20 [unitless] • Bin 2: 21 – 40 [unitless] • Bin 3: 41 – 60 [unitless] • Bin 4: 61 – 80 [unitless] • Bin 5: 81 – 100 [unitless] Files data_10min_WIBS_Conc.csv Header: - NumberConcentrationA[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel A, measured in particles per cubic centimeter. - NumberConcentrationB[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel B, measured in particles per cubic centimeter. - NumberConcentrationC[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel C, measured in particles per cubic centimeter. - NumberConcentrationAB[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and B, measured in particles per cubic centimeter. - NumberConcentrationBC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels B and C, measured in particles per cubic centimeter. - NumberConcentrationAC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and C, measured in particles per cubic centimeter. - NumberConcentrationABC[/cm3]: Combined number concentration of bioaerosol particles detected by all three fluorescence channels A, B, and C, measured in particles per cubic centimeter. - NumberConcentrationNFBAP[/cm3]: Number concentration of non-fluorescent bioaerosol particles, measured in particles per cubic centimeter. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Files data_10min_WIBS_SizeDist.csv Header: - FBAP_SizeDist[/cm3]_Bin_1 to FBAP_SizeDist[/cm3]_Bin_26: Number concentrations of FBAP in each of 26 size bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle sizes, capturing the size distribution of FBAPs detected during the measurement. - NFBAP_SizeDist[/cm3]_Bin_1 to NFBAP_SizeDist[/cm3]_Bin_26: Number concentrations of NFBAP in each of 26 size bins, measured in particles per cubic centimeter. Similar to FBAP, each bin covers a specific range of particle sizes, detailing the size distribution of NFBAPs detected. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Size Bins: • Bin 1: 0.48 to 0.57 μm • Bin 2: 0.57 to 0.67 μm • Bin 3: 0.67 to 0.79 μm • Bin 4: 0.79 to 0.93 μm • Bin 5: 0.93 to 1.1 μm • Bin 6: 1.1 to 1.29 μm • Bin 7: 1.29 to 1.52 μm • Bin 8: 1.52 to 1.8 μm • Bin 9: 1.8 to 2.11 μm • Bin 10: 2.11 to 2.5 μm • Bin 11: 2.5 to 2.94 μm • Bin 12: 2.94 to 3.46 μm • Bin 13: 3.46 to 4.08 μm • Bin 14: 4.08 to 4.81 μm • Bin 15: 4.81 to 5.67 μm • Bin 16: 5.67 to 6.68 μm • Bin 17: 6.68 to 7.88 μm • Bin 18: 7.88 to 9.29 μm • Bin 19: 9.29 to 10.96 μm • Bin 20: 10.96 to 12.92 μm • Bin 21: 12.92 to 15.23 μm • Bin 22: 15.23 to 17.96 μm • Bin 23: 17.96 to 21.17 μm • Bin 24: 21.17 to 24.96 μm • Bin 25: 24.96 to 29.43 μm • Bin 26: 29.43 to 34.70 μm

54 ENVIRONMENTAL SCIENCES↗