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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Pulmonary decompression sickness at altitude: early symptoms and circulating gas emboli

INTRODUCTION: Pulmonary altitude decompression sickness (DCS) is a rare condition. 'Chokes' which are characterized by the triad of substernal pain, cough, and dyspnea, are considered to be associated with severe accumulation of gas bubbles in the pulmonary capillaries and may rapidly develop into a life-threatening medical emergency. This study was aimed at characterizing early symptomatology and the appearance of venous gas emboli (VGE). METHODS: Symptoms of simulated-altitude DCS and VGE (with echo-imaging ultrasound) were analyzed in 468 subjects who participated in 22 high altitude hypobaric chamber research protocols from 1983 to 2001 at Brooks Air Force Base, TX. RESULTS: Of 2525 subject-exposures to simulated altitude, 1030 (41%) had symptoms of DCS. Only 29 of those included DCS-related pulmonary symptoms. Of these, only 3 subjects had all three pulmonary symptoms of chokes; 9 subjects had two of the pulmonary symptoms; and 17 subjects had only one. Of the 29 subject-exposures with pulmonary symptoms, 27 had VGE and 21 had severe VGE. The mean onset times of VGE and symptoms in the 29 subject-exposures were 42 +/- 30 min and 109 +/- 61 min, respectively. In 15 subjects, the symptoms disappeared during recompression to ground level followed by 2 h of oxygen breathing. In the remaining 14 cases, the symptoms disappeared with immediate hyperbaric oxygen treatment. CONCLUSIONS: Pulmonary altitude DCS or chokes is confirmed to be a rare condition. Our data showed that when diagnosed early, recompression to ground level pressure and/or hyperbaric oxygen treatment was 100% successful in resolving the symptoms.

Non-NASA Center↗
DOE OSTI2014

Quantitative Assessment of Detection Frequency for the INL Ambient Air Monitoring Network

A quantitative assessment of the Idaho National Laboratory (INL) air monitoring network was performed using frequency of detection as the performance metric. The INL air monitoring network consists of 37 low-volume air samplers in 31 different locations. Twenty of the samplers are located on INL (onsite) and 17 are located off INL (offsite). Detection frequencies were calculated using both BEA and ESER laboratory minimum detectable activity (MDA) levels. The CALPUFF Lagrangian puff dispersion model, coupled with 1 year of meteorological data, was used to calculate time-integrated concentrations at sampler locations for a 1-hour release of unit activity (1 Ci) for every hour of the year. The unit-activity time-integrated concentration (TICu) values were calculated at all samplers for releases from eight INL facilities. The TICu values were then scaled and integrated for a given release quantity and release duration. All facilities modeled a ground-level release emanating either from the center of the facility or at a point where significant emissions are possible. In addition to ground-level releases, three existing stacks at the Advanced Test Reactor Complex, Idaho Nuclear Technology and Engineering Center, and Material and Fuels Complex were also modeled. Meteorological data from the 35 stations comprising the INL Mesonet network, data from the Idaho Falls Regional airport, upper air data from the Boise airport, and three-dimensional gridded data from the weather research forecasting model were used for modeling. Three representative radionuclides identified as key radionuclides in INL’s annual National Emission Standards for Hazardous Air Pollutants evaluations were considered for the frequency of detection analysis: Cs-137 (beta-gamma emitter), Pu-239 (alpha emitter), and Sr-90 (beta emitter). Source-specific release quantities were calculated for each radionuclide, such that the maximum inhalation dose at any publicly accessible sampler or the National Emission Standards for Hazardous Air Pollutants maximum exposed individual location (i.e., Frenchman’s Cabin) was no more than 0.1 mrem yr–1 (i.e., 1% of the 10 mrem yr–1 standard). Detection frequencies were calculated separately for the onsite and offsite monitoring network. As expected, detection frequencies were generally less for the offsite sampling network compared to the onsite network. Overall, the monitoring network is very effective at detecting the potential releases of Cs-137 or Sr-90 from all sources/facilities using either the ESER or BEA MDAs. The network was less effective at detecting releases of Pu-239. Maximum detection frequencies for Pu-239 using ESER MDAs ranged from 27.4 to 100% for onsite samplers and 3 to 80% for offsite samplers. Using BEA MDAs, the maximum detection frequencies for Pu-239 ranged from 2.1 to 100% for onsite samplers and 0 to 5.9% for offsite samplers. The only release that was not detected by any of the samplers under any conditions was a release of Pu-239 from the Idaho Nuclear Technology and Engineering Center main stack (CPP-708). The methodology described in this report could be used to improve sampler placement and detection frequency, provided clear performance objectives are defined.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2013

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Nitrogen dioxide↗
NASA NTRS1993

An expert system shell for inferring vegetation characteristics: Atmospheric techniques (Task G)

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG Subgoals have been reorganized into categories. A new subgoal category 'Atmospheric Techniques' containing two new subgoals has been implemented. The subgoal Atmospheric Passes allows the scientist to take reflectance data measured at ground level and predict what the reflectance values would be if the data were measured at a different atmospheric height. The subgoal Atmospheric Corrections allows atmospheric corrections to be made to data collected from an aircraft or by a satellite to determine what the equivalent reflectance values would be if the data were measured at ground level. The report describes the implementation and testing of the basic framework and interface for the Atmospheric Techniques Subgoals.

Harrison, P. Ann↗
NASA NTRS2004

Web-Based Toxic Gas Dispersion Model for Shuttle Launch Operations

During the launch of the Space Shuttle vehicle, the burning of liquid hydrogen fuel with liquid oxygen at extreme high temperatures inside the three space shuttle main engines, and the burning of the solid propellant mixture of ammonium perchlorate oxidizer, aluminum fuel, iron oxide catalyst, polymer binder, and epoxy curing agent in the two solid rocket boosters result in the formation of a large cloud of hot, buoyant toxic exhaust gases near the ground level which subsequently rises and entrains into ambient air until the temperature and density of the cloud reaches an approximate equilibrium with ambient conditions. In this paper, toxic gas dispersion for various gases are simulated over the web for varying environmental conditions which is provided by rawinsonde data. The model simulates chemical concentration at ground level up to 10 miles (1 KM grids) in downrange up to an hour after launch. The ambient concentration of the gas dispersion and the deposition of toxic particles are used as inputs for a human health risk assessment model. The advantage of the present model is the accessibility and dissemination of model results to other NASA centers over the web. The model can be remotely operated and various scenarios can be analyzed.

Bardina, Jorge↗
DOE OSTI2018

Agricultural Burning and Air Quality over Northern India: A Synergistic Analysis using NASA’s A-train Satellite Data and Ground Measurements

In recent years, New Delhi, the capital city of India, has been ranked among the most polluted cities in the world in terms of air quality related to Particulate Matter (PM). In this paper, we show that the PM 2.5 , a major component of the measure of air quality, over New Delhi is strongly impacted by the agricultural fires in the north-western Indian states of Punjab and Haryana during the post-monsoon season (October and November). Using data from NASA’s A-train sensors (MODIS, OMI, and CALIOP) in conjunction with the ground-level PM 2.5 mass concentration measured at the US Embassy site in New Delhi (2013-2015), and back-trajectory analysis, it is shown that the smoke particles produced from numerous fires in Punjab and Haryana are advected over the national capital region under the influence of north-westerly winds, thereby greatly increasing the ground-level PM 2.5 from 50 µg/m -3 before the onset of burning in early October to as high as 300 µg/m -3 (24-hour averaged, 7-day running mean) during the peak burning period in early November. Relationships between the satellite measurements of fire counts and aerosols in the crop burning region and PM 2.5 over New Delhi are found to be strongly correlated. A linear regression analysis reveals that increments in the fire counts, aerosol optical depth, UV Aerosol Index, and aerosol absorption optical depth by 100, 1.0, 1.0, and 0.1 over the burning areas result in an increase in PM 2.5 by 20, 47, 134, and 142 µg/m -3 , respectively, over New Delhi. Back-trajectory analysis shows that about 74%, 62%, and 51% of total number of daily trajectories for altitudes 10 m, 500 m, and 1500 m, respectively, intercepted the biomass burning region before arriving at the receptor location in New Delhi; this further corroborates the transport mechanism observed in the satellite data. A 15-year long record of A-train satellite measurements shows an increasing number of agricultural fires (29% higher) and aerosol loading during the second half of the record (2009-2015) compared to that during the first half (2002-2008), which is one of the major concerns for the deteriorating air quality in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Ground-based observation of clusters and nucleation-mode particles in the Amazon

We investigated atmospheric new particle formation (NPF) in the Amazon rainforest using direct measurement methods. To our knowledge this is the first direct observation of NPF events in the Amazon region. However, previous observations elsewhere in Brazil showed the occurrence of nucleation-mode particles. Here, our measurements covered two field sites and both the wet and dry season. We measured the variability of air ion concentrations (0.8–12nm) with an ion spectrometer between September 2011 and January 2014 at a rainforest site (T0t). Between February and October 2014, the same measurements were performed at a grassland pasture site (T3) as part of the GoAmazon 2014/5 experiment, with two intensive operating periods (IOP1 and IOP2 during the wet and the dry season, respectively). The GoAmazon 2014/5 experiment was designed to study the influence of anthropogenic emissions on the changing climate in the Amazon region. The experiment included basic aerosol and trace gas measurements at the ground, remote sensing instrumentation, and two aircraft-based measurements.The results presented in this work are from measurements performed at ground level at both sites. The site inside the rainforest (T0t) is located 60km NNW of Manaus and influenced by pollution about once per week. The pasture (T3) site is located 70km downwind from Manaus and influenced by the Manaus pollution plume typically once per day or every second day, especially in the afternoon. No NPF events were observed inside the rainforest (site T0t) at ground level during the measurement period. However, rain-induced ion and particle bursts (hereafter, rain events) occurred frequently (643 of 1031 days) at both sites during the wet and dry season, being most frequent during the wet season. During the rain events, the ion concentrations in three size ranges (0.8–2, 2–4, and 4–12nm) increased up to about 10 4 –10 5 cm -3 . This effect was most pronounced in the intermediate and large size ranges, for which the background ion concentrations were about 10–15cm -3 compared with 700 cm -3 for the cluster ion background. We observed eight NPF events at the pasture site during the wet season. We calculated the growth rates and formation rates of neutral particles and ions for the size ranges 2–3 and 3–7 nm using the ion spectrometer data. The observed median growth rates were 0.8 and 1.6nmh -1 for 2–3nm sized ions and particles, respectively, with larger growth rates (13.3 and 7.9 nmh -1 ) in the 3–7 nm size range. The measured nucleation rates were of the order of 0.2 cm -3 s -1 for particles and 4–9×10 -3 cm -3 s -1 for ions. There was no clear difference in the sulfuric acid concentrations between the NPF event days and nonevent days (~9×10 5 cm -3 ). The two major differences between the NPF days and nonevent days were a factor of 1.8 lower condensation sink on NPF event days (1.8×10 -3 s -1 ) compared to nonevents (3.2 × 10 -3 s -1 ) and different air mass origins. In conclusion, to our knowledge, this is the first time that results from ground-based sub-3nm aerosol particle measurements have been obtained from the Amazon rainforest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Multiconfiguration Dirac–Hartree–Fock energy levels, weighted oscillator strengths, transitions probabilities, lifetimes, hyperfine constants, Landé g-factors and isotope shifts of Xe LIII

Energy levels, weighted oscillator strengths and transition probabilities, lifetimes, hyperfine interaction constants, Landé g{sub J} factors and isotope shifts are calculated for all levels of 1s{sup 2} and 1snl (n=2−7) configurations of He-like xenon ion (Xe LIII). Multiconfigurational Dirac–Hartree–Fock (MCDHF) method is adopted for calculating these spectroscopic data. Comparisons are made with similar data obtained with FAC (Flexible Atomic Code) to assess the accuracy of the results. Transition probabilities are reported for all E1, E2, M1 and M2 transitions from the ground level. Breit interactions and quantum electrodynamics effects are estimated in extensive Relativistic Configuration Interaction (RCI) calculations. Comparisons were made with the available data in the literature and good agreement was found which confirms the reliability of our results. The accuracy of the present calculations is high enough to facilitate identification of many observed spectral lines. Almost all atomic data of He-like xenon ion presented in this paper are calculated for the first time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Effects of Low-Carbon Energy Adoption on Airborne Particulate Matter Concentrations With Feedbacks to Future Climate Over California

California plans to reduce emissions of long-lived greenhouse gases (GHGs) through adoption of new energy systems that will also lower concentrations of short-lived absorbing soot contained in airborne particulate matter (PM). Here we examine the direct and indirect effects of reduced PM concentrations under a low-carbon energy (GHG-Step) scenario on radiative forcing in California. Simulations were carried out using the source-oriented WRF/Chem (SOWC) model with 12 km spatial resolution for the year 2054. Furthermore, the avoided aerosol emissions due to technology advances in the GHG-Step scenario reduce ground level PM concentrations by ~8.85% over land compared to the Business-as-Usual (BAU) scenario, but changes to meteorological parameters are more modest. Top-of-atmospheric forcing predicted by the SOWC model increased by 0.15 W m -2 , surface temperature warmed by 0.001 K, and planetary boundary layer height (PBLH) increased by 2.20 cm in the GHG-Step scenario compared to the BAU scenario. PM climate feedbacks are small because the significant changes in ground level PM concentrations associated with the GHG-Step scenario are limited to the first few hundred meters of the atmosphere, with little change for the majority of the vertical column above that level. As an order-of-magnitude comparison, the long-term effects of global reductions in GHG emissions (RCP8.5–RCP4.5) lowered average surface temperature over the California study domain by approximately 0.76 K. The effects of long-lived climate pollutants such as CO 2 are much stronger than the effects of short-lived climate pollutants such as PM soot over California in the year 2054.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advancing Aerosol Chemical Characterization and Vertical Profiling over the Southern Great Plains Using Uncrewed Aerial Sampling and Offline Aerosol Mass Spectrometry

Recent advancements in uncrewed aerial systems (UASs) and particulate matter (PM) analytical techniques have provided opportunities for atmospheric research. In this study, we deployed the Department of Energy’s fixed-wing ArcticShark UAS to examine PM 2.5 composition at varying altitudes─within and above the planetary boundary layer (PBL)─over the Southern Great Plains atmospheric observatory (SGP). A total of 22 flights were conducted across March, June, and August 2023. Composite filter samples were collected during each flight and analyzed with offline aerosol mass spectrometry (AMS), complemented by on-board real-time sensors and ground-based instrumentation, to provide a comprehensive view of regional aerosol characteristics. Results show clear vertical and seasonal differences in the aerosol composition. Relative to ground-level measurements, aloft samples exhibited shifts in the distribution of organic and inorganic PM, with the organic composition varying distinctly across seasons. Particulate organic nitrogen (ON) was elevated, with bulk compositions similar in March and June but strongly altered in August, likely driven by biomass burning and enhanced photochemical activity. Combined AMS and chemical ionization mass spectrometry analyses detected amines, amides, and amino acids. PM above the planetary boundary layer was enriched in oxidized organic aerosols, while ground-level PM contained higher nitrate and sulfate. Seasonal differences in aqueous-phase processing were also observed, which were strongest in March during persistent cloud cover and weaker in the drier August period, suggesting a shift from aqueous- to gas-phase SOA formation. In conclusion, these findings highlight the value of UAS in advancing PM measurements and vertical profiling of aerosol composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Mercury Dispersion Modeling and Purge Ventilation Stack Height Determination for Tank 41H

The SRNL Atmospheric Technologies Group performed an analysis of mercury emissions from H-Tank Farm – Tank 41H ventilation system exhaust to assess worst case 15-minute and 8-hour average ground level concentrations and evaluate whether the Short-Term Exposure Limit (STEL), or Threshold Limit Value (TLV) levels for mercury will be exceeded during mixing operations. This analysis was also used to establish a minimum stack height at which ambient mercury concentration would not exceed the safety limits. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modelling tool for this analysis. Results indicate that a stack height of 30-ft (for the 25 mg/m 3 emissions case) or 50-ft (for the 50 mg/m 3 emissions case) stacks results in ground level concentrations that do not exceed the STEL or TLV standards.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Turbulent Flux Measurements of the Near‐Surface and Residual‐Layer Small Particle Events

Abstract According to recent field studies, almost half of the New Particle Formation (NPF) events occur aloft, in a residual layer, near the top of the boundary layer. Therefore, measurements of the meteorological parameters, precursor gas concentrations, and aerosol loadings conducted at the ground level are often not representative of the conditions where the NPFs take place. This paper presents new measurements obtained during the Turbulent Flux Measurements of the Residual Layer Nucleation Particles, conducted at the Southern Great Plains research site. Vertical turbulent fluxes of 3–10 nm‐sized particles were measured using a sonic anemometer and two condensation particle counters with nominal cutoff diameters of 3 nm and 10 nm mounted at the top of the 10‐m telescoping tower. Aerosol number size distribution (5–300 nm) was determined through the ground‐based Scanning Mobility Particle Sizers. The size selected (15–50 nm) particle hygroscopicity was derived with the Humidified Tandem Differential Mobility Analyzer. The ground level observations were supplemented by vertically‐resolved measurements of horizontal and vertical wind speeds and aerosol backscatter. The data analysis suggests that (a) turbulent flux measurements of 3–10 nm particles can distinguish between near‐surface and residual‐layer small particle events; (b) sub‐50 nm particles had a hygroscopicity value of 0.2, suggesting that organic compounds dominate atmospheric nanoparticle chemical composition at the site; and (c) current methodologies are inadequate for estimating the dry deposition velocity of sub‐10 nm particles because it is not feasible to measure particle concentration very near the surface, in the diffusion sublayer.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these transportation plans will affect fbture air quality.

Quattrochi, Dale A.↗
DOE OSTI2017

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identifi-cation or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

Acciarri, R↗
NASA NTRS2006

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
DOE OSTI2014

Herbivores and nutrients control grassland plant diversity via light limitation.

Human alterations to nutrient cycles1,2 and herbivore communities3–7 are affecting global biodiversity dramatically2. Ecological theory predicts these changes should be strongly counteractive: nutrient addition drives plant species loss through intensified competition for light, whereas herbivores prevent competitive exclusion by increasing ground-level light, particularly in productive systems8,9. Here we use experimental data spanning a globally relevant range of conditions to test the hypothesis that herbaceous plant species losses caused by eutrophication may be offset by increased light availability due to herbivory. This experiment, replicated in 40 grasslands on 6 continents, demonstrates that nutrients and herbivores can serve as counteracting forces to control local plant diversity through light limitation, independent of site productivity, soil nitrogen, herbivore type and climate. Nutrient addition consistently reduced local diversity through light limitation, and herbivory rescued diversity at sites where it alleviated light limitation. Thus, species loss from anthropogenic eutrophication can be ameliorated in grasslands where herbivory increases ground-level light.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2006

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
DOE OSTI2022

Skipper Charge-Coupled Device for Low-Energy-Threshold Particle Experiments above Ground

Here we present experimental results using a single-electron resolution skipper CCD running above ground level to demonstrate the potential of this technology for its use in reactor neutrino observations and other low-energy particle-interaction experiments. Operating conditions and event-selection criteria are provided to decouple most of the background rate at low energies. The majority of this background comes from interactions in the inactive silicon surrounding the active detector volume that ends up in the readout register of the sensor. Our final results are compared with other low-threshold technologies showing a good control of the background for low ionization energies down to five electron-hole pairs. This demonstrates that the skipper CCD proves to be among the best options to measure low-energy and weakly interacting particles at ground level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗