Effect of Humidity on Scintillation Performance in Na and Tl Activated CsI Crystals
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Abstract Increasing hurricane frequency and intensity with climate change is likely to affect soil organic carbon (C) stocks in tropical forests. We examined the cycling of C between soil pools and with depth at the Luquillo Experimental Forest in Puerto Rico in soils over a 30‐year period that spanned repeated hurricanes. We used a nonlinear matrix model of soil C pools and fluxes (“soilR”) and constrained the parameters with soil and litter survey data. Soil chemistry and stable and radiocarbon isotopes were measured from three soil depths across a topographic gradient in 1988 and 2018. Our results suggest that pulses and subsequent reduction of inputs caused by severe hurricanes in 1989, 1998, and two in 2017 led to faster mean transit times of soil C in 0–10 cm and 35–60 cm depths relative to a modeled control soil with constant inputs over the 30‐year period. Between 1988 and 2018, the occluded C stock increased and δ 13 C in all pools decreased, while changes in particulate and mineral‐associated C were undetectable. The differences between 1988 and 2018 suggest that hurricane disturbance results in a dilution of the occluded light C pool with an influx of young, debris‐deposited C, and possible microbial scavenging of old and young C in the particulate and mineral‐associated pools. These effects led to a younger total soil C pool with faster mean transit times. Our results suggest that the increasing frequency of intense hurricanes will speed up rates of C cycling in tropical forests, making soil C more sensitive to future tropical forest stressors.
Presented by NETL at SPIE Defense and Commercial Sensing 2019 meeting, 03/19
The dynamics of the H{sub 2}O molecule density in a metal gas-discharge chamber filled with low-pressure water vapor or its mixtures with noble gases was investigated by manometric and spectral methods. Regimes both with and without discharge excitation were studied. In the absence of a discharge, the molecule density dynamics is governed by the heterogeneous interaction of molecules with the chamber walls. In the presence of a discharge, in addition to the heterogeneous interaction, fast plasmachemical molecule dissociation also contributes to the initial stage of H{sub 2}O molecule loss. The role of heating of the chamber walls is discussed.
Hydroxide exchange membrane fuel cells (HEMFC) are an enticing power source for automobiles due to their low cost. Here we focus on improving the beginning-of-life performance of HEMFCs to a higher level with poly(aryl piperidinium) (PAP) membranes and ionomers. We reveal that lower RH and backpressure in anode than cathode can eliminate anode flooding and cathode dryout so that a balanced water management can be achieved. We also find that PtRu/C is a better anode catalyst than Pt/Ketjen Black due to the presence of Ru and Pt/Vulcan XC-72 is a better cathode catalyst than Pt/Ketjen Black due to its better mass transport properties. Once the preferred operating conditions and materials incorporated into the same cell, our HEMFCs achieved a peak power density of 1.89 W cm –2 in H 2 /O 2 and 1.31 W cm –2 in H 2 /air.
We find that the deadly heat waves in India and Pakistan in 2015 were exacerbated by anthropogenic climate change. Although the impacts of both events were severe, the events themselves were not connected to each other.
Conditional instability and the buoyancy of plumes drive moist convection but have a variety of representations in model convective schemes. Vertical thermodynamic structure information from Atmospheric Radiation Measurement (ARM) sites and reanalysis (ERA5), satellite-derived precipitation (TRMM3b42), and diagnostics relevant for plume buoyancy are used to assess climate models. Previous work has shown that CMIP6 models represent moist convective processes more accurately than their CMIP5 counterparts. However, certain biases in convective onset remain pervasive among generations of CMIP modeling efforts. Here we diagnose these biases in a cohort of nine CMIP6 models with sub-daily output, assessing conditional instability in profiles of equivalent potential temperature θ e and saturation equivalent potential temperature θ es in comparison to a plume model with different mixing assumptions. Most models capture qualitative aspects of the θ es vertical structure, including a substantial decrease with height in the lower free troposphere associated with the entrainment of subsaturated air. We define a “pseudo-entrainment” diagnostic that combines subsaturation and a θ es measure of conditional instability similar to what entrainment would produce under the small-buoyancy approximation. This captures the trade-off between larger θ es lapse rates (entrainment of dry air) and small subsaturation (permits positive buoyancy despite high entrainment). This pseudo-entrainment diagnostic is also a reasonable indicator of the critical value of integrated buoyancy for precipitation onset. Models with poor θ e /θ es structure (those using variants of the Tiedtke Scheme) or low entrainment runs of CAM5, and models with low subsaturation, such as NASA-GISS, lie outside the observational range in this diagnostic.
This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in an urbanized catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, distributed temperature sensing (DTS), continuous self-potential (SP) monitoring, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Field_Application subfolder contains the ATS XML input scripts, data files, output data for the SP site. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. The flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.m can only be used with COMSOL with MATLAB) is executed using the ATS output data to simulate the potential field. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) DTS Contains collated DTS data including raw Stokes and anti-Stokes measurement (provided as .h5 file). It also includes DTS processing.ipynb, a Jupyter notebook for calibrating the DTS data using dts_calibration Python package. cooler_calibration.csv is the DTS calibration CSV used in the calibration sequence. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion. 6) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 7) SP Contains the SP data collected in field at the SP sites (provided as CSV files). 8) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). Note: Code files (.ipynb, .py, .xml) can be opened in any standard code editor, .exo file can be viewed using Paraview, .h5 files can be opened using HDFView software and h5py Python package, and .resipy file can be opened with the open-source ResIPy software.
This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.
This data package contains raw data from stomatal conductance and leaf temperature measurements from the K34 tower in Manaus, Brazil. The attached zip file contains one data file and two metadata files. Related data packages, including additional metadata such as site information and equipment manuals, are listed under Dataset Reference(s). Contact israelmdt@gmail.com if you need to use this dataset for additional information.
Under this project, Newport Partners (as part of the BA-PIRC research team) evaluated the installation, measured performance, and cost-effectiveness of efficiency upgrade measures for a tenant-in-place DER at the Bay Ridge multifamily (MF) development in Annapolis, Maryland. The design and construction phase of the Bay Ridge project was completed in August 2012. This report summarizes system commissioning, short-term test results, utility bill data analysis, and analysis of real-time data collected over a one-year period after the retrofit was complete. The Bay Ridge project is comprised of a 'base scope' retrofit which was estimated to achieve a 30%+ savings (relative to pre-retrofit) on 186 apartments, and a 'DER scope' which was estimated to achieve 50% savings (relative to pre-retrofit) on a 12-unit building. The base scope was applied to the entire apartment complex, except for one 12-unit building which underwent the DER scope. A wide range of efficiency measures was applied to pursue this savings target for the DER building, including improvements/replacements of mechanical equipment and distribution systems, appliances, lighting and lighting controls, the building envelope, hot water conservation measures, and resident education. The results of this research build upon the current body of knowledge of multifamily retrofits. Towards this end, the research team has collected and generated data on the selection of measures, their estimated performance, their measured performance, and risk factors and their impact on potential measures.
The ZEBRAlliance is an opportunity to accelerate progress toward DOE’s goal of maximizing cost-effective energy efficiency by investing in a highly leveraged, focused effort to test new high-efficiency components emerging from Oak Ridge National Laboratory’s (ORNL) Cooperative Research and Development Agreement (CRADA) partners and others. The Alliance integrated efficient components into the construction of four research houses that will be used as test markets to gauge the success of the components and houses. These four research houses are expected to be the first houses used to field-test several newly emerging products such as the ClimateMaster ground-source integrated heat pump. When these new components are proven, they will become available to serve regional and national homebuilding markets. Some of these products will impact existing housing retrofit markets as well as new construction. These four houses demonstrate different strategies for saving energy, but all are about 55-60% more efficient than traditional new construction (based on third party certified HERS evaluations). After the research period, the houses will be sold to interested home buyers. The outcome will contribute to efforts by TVA to defer 1,400 MW of new electricity generation and reduce growth in energy consumption by 4.3 million MWh per year by 2012, and in the longer term, to transform how homes are built and retrofitted for improved energy efficiency in the Tennessee Valley.
Under this project, Newport Partners (as part of the BA-PIRC research team) evaluated the installation, measured performance, and cost-effectiveness of efficiency upgrade measures for a tenant-in-place DER at the Bay Ridge multifamily (MF) development in Annapolis, Maryland. The design and construction phase of the Bay Ridge project was completed in August 2012. This report summarizes system commissioning, short-term test results, utility bill data analysis, and analysis of real-time data collected over a one-year period after the retrofit was complete. The Bay Ridge project is comprised of a "base scope" retrofit which was estimated to achieve a 30%+ savings (relative to pre-retrofit) on 186 apartments, and a "DER scope" which was estimated to achieve 50% savings (relative to pre-retrofit) on a 12-unit building. The base scope was applied to the entire apartment complex, except for one 12-unit building which underwent the DER scope. A wide range of efficiency measures was applied to pursue this savings target for the DER building, including improvements/replacements of mechanical equipment and distribution systems, appliances, lighting and lighting controls, the building envelope, hot water conservation measures, and resident education. The results of this research build upon the current body of knowledge of multifamily retrofits. Towards this end, the research team has collected and generated data on the selection of measures, their estimated performance, their measured performance, and risk factors and their impact on potential measures.
Kohl's Department Stores partnered with the U.S. Department of Energy (DOE) to develop and implement solutions to build new stores that consume at least 50% less than the requirements set by ASHRAE/ANSI/IESNA Standard 90.1-20041 as part of DOE's Commercial Building Partnership (CBP) program. The National Renewable Energy Laboratory (NREL) provided technical expertise on the project.