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

COVID-19–Related School Closures, United States, July 27, 2020–June 30, 2022

As part of a multiyear project that monitored illness-related school closures, we conducted systematic daily online searches during July 27, 2020–June 30, 2022, to identify public announcements of COVID-19–related school closures (COVID-SCs) in the United States lasting ≥1 day. We explored the temporospatial patterns of COVID-SCs and analyzed associations between COVID-SCs and national COVID-19 surveillance data. COVID-SCs reflected national surveillance data: correlation was highest between COVID-SCs and both new PCR test positivity (correlation coefficient [r] = 0.73, 95% CI 0.56–0.84) and new cases (r = 0.72, 95% CI 0.54–0.83) during 2020–21 and with hospitalization rates among all ages (r = 0.81, 95% CI 0.67–0.89) during 2021–22. The numbers of reactive COVID-SCs during 2020–21 and 2021–22 greatly exceeded previously observed numbers of illness-related reactive school closures in the United States, notably being nearly 5-fold greater than reactive closures observed during the 2009 influenza (H1N1) pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Genomic-based biosurveillance for avian influenza: whole genome sequencing from wild mallards sampled during autumn migration in 2022–2023 reveals a high co-infection rate on migration stopover site in Georgia

The Caucasus region, including Georgia, is an important intersection for migratory waterbirds, offering potential for avian influenza virus (AIV) transmission between populations from different geographic areas. In 2022 and 2023, wild ducks were sampled during autumn migration events in Georgia to study the genetic relationships and molecular characteristics of influenza strains. Sequencing and phylogenetic analysis were used to compare the sampled strains to reference sequences from Africa, Asia, and Europe, allowing assessment of genetic relationships and virus transmission between migratory birds. Protein language modeling identified potential co-infections. Of 225 duck samples, 128 tested positive for the influenza M gene. 55 influenza-positive samples underwent whole-genome sequencing, revealing significant diversity. Analysis of the hemagglutinin (HA) segment showed notable differences among subtypes. Most samples were H6N1 and H6N6, but co-infections with combinations like H6H3, N8N1, N6H9, N2N6, and H9H6/N1N2 were also identified. These findings demonstrate the high variability of influenza viruses in migratory waterbirds in Georgia, including a notable rate of co-infections. Some samples exhibited uncommon genetic characteristics compared to other strains from the same year, suggesting Georgia’s role as a mixing vessel for influenza viruses. This facilitates reassortment during co-infections and contributes to the genetic diversity observed across flyways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The rapid change in mental health among college students after introduction of on-campus quarantine during the 2022 Shanghai COVID-19 lockdown

Objectives Among the various impacts of disasters in terms of emotions, quarantine has been proven to result in significant increases in mental health problems. Studies of psychological resilience during outbreaks of epidemics tend to focus on long-term social quarantine. In contrast, insufficient studies have been conducted examining how rapidly negative mental health outcomes occur and how these outcomes change over time. We evaluated the time course of psychological resilience (over three different phases of quarantine) among students at Shanghai Jiao Tong University to investigate the influence of unexpected changes on college students. Methods An online survey was conducted from 5 to 7 April 2022. A structured online questionnaire was administered using a retrospective cohort trial design. Before 9 March (Period 1), individuals engaged in their usual activities without restrictions. From 9 to 23 March (Period 2), the majority of students were asked to remain in their dormitories on campus. From 24 March to early April (Period 3), restrictions were relaxed, and students were gradually allowed to participate in essential activities on campus. We quantified dynamic changes in the severity of students’ depressive symptoms over the course of these three periods. The survey consisted of five sets of self-reported questions: demographic information, lifestyle/activity restrictions, a brief mental health history, COVID-19-related background, and the Beck Depression Inventory, second edition. Results A total of 274 college students aged 18–42 years (mean = 22.34; SE = 0.24) participated in the study (58.39% undergraduate students, 41.61% graduate students; 40.51% male, 59.49% female). The proportion of students with depressive symptoms was 9.1% in Period 1, 36.1% in Period 2, and 34.67% in Period 3. Depressive symptoms increased notably with the introduction of the quarantine in Periods 2 and 3. Lower satisfaction with the food supplied and a longer duration of physical exercise per day were found to be positively associated with changes in depression severity in Periods 2 and 3. Quarantine-related psychological distress was more evident in students who were in a romantic relationship than in students who were single. Conclusion Depressive symptoms in university students rapidly increased after 2 weeks of quarantine and no perceptible reversal was observed over time. Concerning students in a relationship, ways to take physical exercise and to relax should be provided and the food supplied should be improved when young people are quarantined.

Ma, Dongni↗
DOE OSTI2023

Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review

In the past decade, different sensing mechanisms and algorithms have been developed to detect or estimate indoor occupancy. One of the most recent advancements is using networked sensor nodes to create a more comprehensive occupancy detection system where multiple sensors can identify human presence within more expansive areas while delivering enhanced accuracy compared to a system that relies on stand-alone sensor nodes. The present work reviews the studies from 2012 to 2022 that use networked sensor nodes to detect indoor occupancy, focusing on PIR-based sensors. Methods are compared based on pivotal ADPs that play a significant role in selecting an occupancy detection system for applications such as Health and Safety or occupant comfort. These parameters include accuracy, information requirement, maximum sensor failure and minimum observation rate, and feasible detection area. We briefly describe the overview of occupancy detection criteria used by each study and introduce a metric called “sensor node deployment density” through our analysis. This metric captures the strength of network-level data filtering and fusion algorithms found in the literature. It is hinged on the fact that a robust occupancy estimation algorithm requires a minimal number of nodes to estimate occupancy. This review only focuses on the occupancy estimation models for networked sensor nodes. It thus provides a standardized insight into networked nodes’ occupancy sensing pipelines, which employ data fusion strategies, network-level machine learning algorithms, and occupancy estimation algorithms. This review thus helps determine the suitability of the reviewed methods to a standard set of application areas by analyzing their gaps.

Emad-Ud-Din, Muhammad (ORCID:0000000279515538)↗
DOE OSTI2023

The 2022 High-energy Outburst and Radio Disappearing Act of the Magnetar 1E 1547.0–5408

We report the radio and high-energy properties of a new outburst from the radio-loud magnetar 1E 1547.0–5408. Following the detection of a short burst from the source with Swift-BAT on 2022 April 7, observations by NICER detected an increased flux peaking at (6.0 ± 0.4) × 10 –11 erg s –1 cm –2 in the soft X-ray band, falling to a baseline level of 1.7 × 10 –11 erg s –1 cm –2 over a 17 day period. Joint spectroscopic measurements by NICER and NuSTAR indicated no change in the hard nonthermal tail despite the prominent increase in soft X-rays. Observations at radio wavelengths with Murriyang, the 64 m Parkes radio telescope, revealed that the persistent radio emission from the magnetar disappeared at least 22 days prior to the initial Swift-BAT detection and was redetected two weeks later. Such behavior is unprecedented in a radio-loud magnetar, and may point to an unnoticed slow rise in the high-energy activity prior to the detected short bursts. Finally, our combined radio and X-ray timing revealed the outburst coincided with a spin-up glitch, where the spin frequency and spin-down rate increased by 0.2 ± 0.1 μHz and (–2.4 ± 0.1) × 10 –12 s –2 , respectively. A linear increase in the spin-down rate of (–2.0 ± 0.1) × 10 –19 s –3 was also observed over 147 days of postoutburst timing. Our results suggest that the outburst may have been associated with a reconfiguration of the quasi-polar field lines, likely signaling a changing twist, accompanied by spatially broader heating of the surface and a brief quenching of the radio signal, yet without any measurable impact on the hard X-ray properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Amplified bottom water acidification rates on the Bering Sea shelf from 1970–2022

The Bering Sea shelf supports a highly productive marine ecosystem that is vulnerable to ocean acidification (OA) due to the cold, carbon-rich waters. Previous observational evidence suggests that bottom waters on the shelf are already seasonally undersaturated with respect to aragonite (i.e. Ω arag <1) and that OA will continue to increase the spatial extent, duration, and intensity of these conditions. Here, we use a regional ocean biogeochemical model to simulate changes in ocean carbon chemistry for the Bering Sea shelf from 1970–2022. Over this timeframe, model results suggest that surface Ω arag decreases by −0.043 per decade and surface pH by −0.014 per decade, comparable to observed global rates of OA. However, bottom water pH decreases at twice the rate of surface pH, while bottom [H + ] decreases at nearly 3 times the rate of surface [H + ]. This amplified bottom water acidification has emerged over the past 25 years and is likely driven by a combination of anthropogenic carbon accumulation and increasing primary productivity and subsurface respiration and remineralization. Due to this enhanced bottom water acidification, the spatial extent of bottom waters with Ω arag <1 has greatly expanded over the past 2 decades, along with pH conditions harmful to red king crab. Interannual variability in surface and bottom Ω arag , pH, and [H + ] has also increased over the past 2 decades, resulting in part from the increased physical climate variability. We also find that the Bering Sea shelf is a net annual carbon sink of 1.1–7.9 Tg C yr −1 , with the range resulting from the difference in the two different atmospheric forcing reanalysis products used. Seasonally, the shelf is a significant carbon sink from April–October but a somewhat weaker carbon source from November–March.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Global Carbon Budget 2022

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-MAP_2022_Neph_scatteringcoefficient

TRACER-MAP operated Jul - Aug 2022 as an ASR and ARM project. TRACER-MAP measured and mapped aerosol, volatile organic compounds, trace gas and select meteorological observations across the Houston domain during TRACER. The dataset has been corrected for truncation error using Bond et al, 2009.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TAMU TRACER Upper Air Radiosonde Data June-September 2022 Southeast Texas

The following dataset relates to the TAMU TRACER radiosonde IOP, which involved launching iMet-4 and iMet-4C radiosonde models from various locations in southeast Texas. The radiosondes were launched between June and September 2022 during the TRACER IOP. Telemetry data for all IOPs were copied using the iMet-OS II software provided by radiosonde manufacturer, Intermet Systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

WRF East River simulation Oct 2021 - Dec 2022

These are the Weather Research and Forecasting (WRF) regional climate model simulations for supporting the analysis of temperature, precipitation, and other hydroclimate variables and evaluating SAIL data. The WRF model has three nested domains centered at the SAIL location (East River, Colorado) for the SAIL period from Oct 01, 2021 to Dec 31, 2022. We used the BSU subgrid-scale physics schemes, CFSR meteorological forcing datasets, and the topographic shading radiation schemes in our WRF simulation. Detailed information on the model configuration can be found at https://doi.org/10.5194/egusphere-2022-437

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER-MAP_2022_absorption_coefficient

Absorption coefficient for PM2.5 measured by the Tri-color Absorption Photometer averaged every 2 minutes for July-August 2022. The location of the measurement is indicated by latitude and longitude coordinates; TRACER-MAP included time at the AMF site in La Porte and additional sites around Houston. Three wavelengths are reported: 365, 520 and 640 nm. The AAE is also reported using the three wavelengths. The data is reported as 2 minute averages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

BIRDIE beryllium-10 and -7 measurements from 2022 summer deep convection rain at ARM SGP

Water samples were manually collected from 11 SGP ARM sites in the early summer of 2022 to measure cosmogenic isotopes of beryllium. The water samples were brought back to the Center for Accelerator Mass Spectrometry (CAMS) at LLNL and analysed for beryllium-10 and beryllium-7 as well as for chlorine-37, chlorine-36, and tritium. A total of six storm events were measured over three weeks. At least five of those storms included overshooting cloud events. Available data include precipitation amount, beryllium-10 concentration, beryllium-7 concentration, and 10/7Be ratio. Spatial and temporal variability in the cosmogenic isotopes was relatively high but could not directly be linked to precipitation amount. Analysis is on-going to explain the measured variability and to see if it can be linked to cloud top height and overshooting depth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VISSS Raw data from SAIL at Gothic from November 2022 to June 2023

A Video in situ Snowfall Sensor (VISSS) records shadow images of precipitating hydrometeors from two perspective at a 90 degree angle with a frequency of 140 Hz. From this, hydrometeor properties such as particle size, shape, complexity, degree of riming, and fall velocity can be derived. The VISSS was set up next to the ARM mobile facility during the SAIL project located in the East River Watershed near Crested Butte, Colorado from November 2022 to June 2023. The deployment was funded by the CORSIPP project (Characterization of orography-influenced riming and secondary ice production and their effects on precipitation rates using radar polarimetry and Doppler spectra) funded by the German Research Foundation (DFG). More information about the VISSS can be found in Maahn et al. 2023 ( https://dx.doi.org/10.5194/egusphere-2023-655 )

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

TRACER-MAP_2022_volatile_organic_compounds_PTRMS

VOCs collected by quadrupole proton transfer reaction mass spectrometry for July-August 2022. A description of this instrument is included in the related publication. The location of the measurement is indicated by latitude and longitude coordinates; TRACER-MAP included time at the AMF site in La Porte and additional sites around Houston. Data below the minimum detection limit are not included here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

End-of-Winter Snow Depth, Temperature, Density, and SWE Measurements at Teller Road Site, Seward Peninsula, Alaska, 2022

Measurements of end-of-winter snow properties were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) from March 28 to April 1, 2022. This dataset contains three *.csv data files of spatially distributed values of snow depth, snow water equivalent (SWE), and temperature at the snow surface and at the bottom of the snowpack. Data were collected toward the end of the winter season from late March to early April, when the snowpack would be near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used to improve collection efficiency and enhance spatial coverage. A user guide included as a *.pdf. This dataset is a continuation of the previous end-of-winter snow surveys conducted at the Teller Road Site in 2016-2018 (Wilson et al., 2020; https://doi.org/10.5440/1592103) and 2019 (Bennett et al., 2021; https://doi.org/10.5440/1798170). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

End-of-Winter Snow Depth, Temperature, Density, and SWE Measurements at Kougarok Road Site, Seward Peninsula, Alaska, 2022

Measurements of end-of-winter snow properties were collected at the NGEE Arctic Kougarok Road Site at mile marker 64 (KG_MM64) from April 2 to April 5, 2022. This dataset contains three *.csv data files of spatially distributed values of snow depth, snow water equivalent (SWE), and snow temperature at the snow surface and at the bottom of the snowpack. Data were collected toward the end of the winter season during early April, when the snowpack would be near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used to improve collection efficiency and enhance spatial coverage. A user guide is included as a *.pdf. This dataset is a continuation of the previous end-of-winter snow surveys conducted at the Kougarok Road Site in 2018 (Wilson et al., 2021; https://doi.org/10.5440/1593874).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NGEE Arctic Rainfall Simulator Validation Data from Los Alamos National Laboratory, New Mexico, Summer 2022

Experiments evaluating the uniformity and intensity of rainfall produced by the NGEE Arctic Rainfall Simulator (NARS) were conducted at Los Alamos National Laboratory, New Mexico, over summer 2022. Petri dishes were placed in a grid within the NARS plot. Simulated rainfall was collected in each petri dish and the intensity and uniformity of the simulator was subsequently calculated. This data package contains two .csv files, one that summarizes the rainfall intensity and uniformity for each experiment, the other that contains individual petri dish water volume and intensity for each plot location and experiment. The Python scripts to control NARS are also included. The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Rain intensity control and data collection are automated using a Raspberry Pi microcomputer. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Air temperature, Utqiagvik (Barrow), Alaska, July 15-17, 2022

Air temperature measured at 15 minute intervals using a HOBO 64K Pendant UA-001-64 housed in a solar radiation shield. Data were collected 15-27 July 2022, on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. The data package files are in .csv format, and include a data file and metadata file. These data were collected in support of stomatal response gas exchange measurements collected during this time period. See related data packages for leaf gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), and phenocamera images collected at the same time and location. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗