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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts

The feasibility of a hurricane initialization framework based on the Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (GSI-4DEnVar) hybrid data assimilation system for the Hurricane Weather Research and Forecasting model (HWRF) model is evaluated in this study. The system considers the temporal evolution of error covariances via the use of four-dimensional ensemble perturbations that are provided by high-resolution, self-consistent HWRF ensemble forecasts. It is different from the configuration of the GSI-based three-dimensional ensemble-variational (GSI-3DEnVar) hybrid data assimilation system, similar to that used in the operational HWRF, which employs background error covariances provided by coarser-resolution global ensembles from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble Kalman filtering data assimilation system. In addition, our proposed initialization framework discards the empirical intensity correction in the vortex initialization package that is employed by the GSI-3DEnVar initialization framework in operational HWRF. Data assimilation and numerical simulation experiments for Hurricanes Joaquin (2015), Patricia (2015), and Matthew (2016) are conducted during their intensity changes. The impacts of two initialization frameworks on the HWRF analyses and forecasts are compared. It is found that GSI-4DEnVar leads to a reduction in track, minimum sea level pressure (MSLP), and maximum surface wind (MSW) forecast errors in all of the HWRF simulations, compared with the GSI-3DEnVar initialization framework. With assimilating high-resolution observations within the hurricane inner-core region, GSI-4DEnVar can produce the initial hurricane intensity reasonably well without the empirical vortex intensity correction. Further diagnoses with Hurricane Joaquin indicate that GSI-4DEnVar can significantly alleviate the imbalances in the initial conditions and enhance the performance of the data assimilation and subsequent hurricane intensity and precipitation forecasts

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Single Quadrupole Multiple Fragment Ion Monitoring Quantitative Mass Spectrometry

Single quadrupole mass spectrometry (MS) with enhanced in-source multiple fragment ion monitoring was designed to perform high sensitivity quantitative mass analyses. Enhanced in-source fragmentation amplifies fragmentation from traditional soft electrospray ionization producing fragment ions that have been found to be identical to those generated in tandem MS. We have combined enhanced in-source fragmentation data with criteria established by the European Union Commission Directive 2002/657/EC for electron ionization single quadrupole quantitative analysis to perform quantitative analyses. These experiments were performed on multiple types of complex samples that included a mixture of 50 standards, as well as cell and plasma extracts. The dynamic range for these quantitative analyses was comparable to triple quadrupole multiple reaction monitoring (MRM) analyses at up to 5 orders of magnitude with the cell and plasma extracts showing similar matrix effects across both platforms. Amino acid and fatty acid measurements performed from certified NIST 1950 plasma with isotopically labeled standards demonstrated accuracy in the range of 91–110% for the amino acids, 76–129% for the fatty acids, and good precision (coefficient of variation <10%). To enhance specificity, a newly developed correlated ion monitoring algorithm was designed to facilitate these analyses. This algorithm autonomously processes, aligns, filters, and compiles multiple ions within one chromatogram enabling both precursor and in-source fragment ions to be correlated within a single chromatogram, also enabling the detection of coeluting species based on precursor and fragment ion ratios. Single quadrupole instrumentation can provide MRM level quantitative performance by monitoring/correlating precursor and fragment ions facilitating high sensitivity analysis on existing single quadrupole instrumentation that are generally inexpensive, easy to operate, and technically less complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Aerosol measurements from earth orbiting spacecraft

The global aerosol data base evolving from monitoring being done by Stratospheric Aerosol Measurement (SAM) II and Stratospheric Aerosol and Gas Experiment (SAGE) since the fall of 1978 is presented. Data reveal that polar stratospheric clouds (PSC) enhance extinction and optical depths by up to two orders of magnitude and an order of magnitude, respectively. These data are over background 1000 nm values of approximately 1.2 x 10 to the -4th per km, and 1.3 x 10 to the -3rd, respectively. SAGE has offered, for the first time, quantitative measurements of volcanic eruptions on a nearly global basis, and estimates are given for the amount of aerosol injected into the stratosphere from each volcano. For example, Northern Hemisphere aerosol was enhanced by more than 100% by the 1980 eruption of Mount St. Helens, which produced about 0.32 x 10 to the 6th metric tons of aerosol. A cirrus cloud data base is being developed which will be useful in earth radiation and water vapor budget studies. Cross-section, contour, and temperature variation diagrams are included.

Mccormick, M. P.↗
DOE OSTI2022

Deep Realistic Extragalactic Model (DREaM) Galaxy Catalogs: Predictions for a Roman Ultra-deep Field

In the next decade, deep galaxy surveys from telescopes such as the James Webb Space Telescope and Roman Space Telescope will provide transformational data sets that will greatly enhance the understanding of galaxy formation during the epoch of reionization (EoR). In this work, we present the Deep Realistic Extragalactic Model (DREaM) for creating synthetic galaxy catalogs. Our model combines dark matter simulations, subhalo abundance matching and empirical models, and includes galaxy positions, morphologies, and spectral energy distributions. The resulting synthetic catalog extends to redshifts z ~ 12, and galaxy masses log 10 (M/M ⊙ ) = 5 covering an area of 1 deg 2 on the sky. We use DREaM to explore the science returns of a 1 deg 2 Roman ultra-deep field (UDF), and to provide a resource for optimizing ultra-deep survey designs. We find that a Roman UDF to ~30 m AB will potentially detect more than 10 6 M UV < -17 galaxies, with more than 10 4 at redshifts z > 7, offering an unparalleled data set for constraining galaxy properties during the EoR. Our synthetic catalogs and simulated images are made publicly available to provide the community with a tool to prepare for upcoming data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Parathyroid hormone enhances fluid shear-induced [Ca2+]i signaling in osteoblastic cells through activation of mechanosensitive and voltage-sensitive Ca2+ channels

Osteoblasts respond to both fluid shear and parathyroid hormone (PTH) with a rapid increase in intracellular calcium concentration ([Ca2+]i). Because both stimuli modulate the kinetics of the mechanosensitive cation channel (MSCC), we postulated PTH would enhance the [Ca2+]i response to fluid shear by increasing the sensitivity of MSCCs. After a 3-minute preflow at 1 dyne/cm2, MC3T3-E1 cells were subjected to various levels of shear and changes in [Ca2+]i were assessed using Fura-2. Pretreatment with 50 nM bovine PTH(1-34) [bPTH(1-34)] significantly enhanced the shear magnitude-dependent increase in [Ca2+]i. Gadolinium (Gd3+), an MSCC blocker, significantly inhibited the mean peak [Ca2+]i response to shear and shear + bPTH(1-34). Nifedipine (Nif), an L-type voltage-sensitive Ca2+ channel (VSCC) blocker, also significantly reduced the [Ca2+]i response to shear + bPTH(1-34), but not to shear alone, suggesting VSCC activation plays an interactive role in the action of these stimuli together. Activation of either the protein kinase C (PKC) or protein kinase A (PKA) pathways with specific agonists indicated that PKC activation did not alter the Ca2+ response to shear, whereas PKA activation significantly increased the [Ca2+]i response to lower magnitudes of shear. bPTH(1-34), which activates both pathways, induced the greatest [Ca2+]i response at each level of shear, suggesting an interaction of these pathways in this response. These data indicate that PTH significantly enhances the [Ca2+]i response to shear primarily via PKA modulation of the MSCC and VSCC.

Non-NASA Center↗
DOE OSTI2021

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mochi: Composing Data Services for High-Performance Computing Environments

Technology enhancements and the growing breadth of application workflows running on high-performance computing (HPC) platforms drive the development of new data services that provide high performance on these new platforms, provide capable and productive interfaces and abstractions for a variety of applications, and are readily adapted when new technologies are deployed. The Mochi framework enables composition of specialized distributed data services from a collection of connectable modules and subservices. Rather than forcing all applications to use a one-size-fits-all data staging and I/O software configuration, Mochi allows each application to use a data service specialized to its needs and access patterns. This paper introduces the Mochi framework and methodology. The Mochi core components and microservices are described. Examples of the application of the Mochi methodology to the development of four specialized services are detailed. Finally, a performance evaluation of a Mochi core component, a Mochi microservice, and a composed service providing an object model is performed. The paper concludes by positioning Mochi relative to related work in the HPC space and indicating directions for future work.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

The EOSDIS Products Usability for Disaster Response

The focus of the study is to categorize both NRT and standard data products based on applicability to the SDR-defined disaster types. This will identify which datasets from current NASA satellite missions instruments are best suited for disaster response. The distribution metrics of the products that have been used for studying various selected disasters that have occurred over last 5 years will be analyzed that include volume, number of files, number of users, user domains, user country, etc. This data usage analysis will provide information to the data centers staff that can help them develop the functionality and allocate the resources needed for enhanced access and timely availability of the data products that are critical for the time-sensitive analyses.

LANCE↗
DOE OSTI2021

Literature Data on Foam Fracturing Fluid

At the beginning of this project, the Temple team spent significant effort to collect data relevant to foam fracturing. More than 40 articles/reports were found in the open literature that reported the properties of aqueous foams under various testing conditions. The foam properties included viscosity and stability in terms of half-life, while were influenced by the foam quality, shear rate, temperature, pressure, as well as surfactants and additives used in making the foam base solutions. As a result, more than 1100 data points were collected, which are included in a master worksheet named "Literature data on Foam Fracturing Fluid". These data points are organized based on following parameters: 1. Literature source, including authors and publication year 2. Gaseous phase (e.g. CO2, N2) 3. Liquid phase (e.g. tap water, DI water, salt water) 4. Surfactants and their concentrations 6. Additives 7. Foam quality 8. Pressure 9. Temperature 10. Viscosity 11. Foam stability, which was characterized by its half-life: Half-life Foam study data base with data analysis was completed and a webpage is designed hosted on public server at https://surfactant-dashboard.herokuapp.com

15 GEOTHERMAL ENERGY↗
NASA NTRS1974

Is the red arc a good indicator of ionosphere-magnetosphere conditions

Weak red arcs were observed on the two consecutive nights of July 12-13 and July 13-14, 1969, at Richland, Washington, whereas no red arcs were detectable on the nights preceding and following the observations. Satellite (Ogo 6) data of electron temperature and density, low-frequency ac electric field, and suprathermal electron flux corresponding to the conjugate region of Richland show no significant variations during these days. The data show elevated electron temperatures and enhanced low-frequency ac noise levels at the expected red arc position in the neighborhood of the density trough, as indicated by previous observations. The data appear to indicate that the optical criterion of red arc occurrence would lead to the conclusion of significantly different ionosphere-magnetosphere conditions during these four nights, whereas the more detailed in situ data show that the conditions were very similar.

Nagy, A. F.↗
DOE OSTI2022

DETAIL Component Scaling and Methodology Comparison

The purpose of this study was to develop a process to convert input signals from one facility into another by reflecting geometric and environmental settings. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is a research facility in development. Its aim is to emulate the daily interactions among power production industry systems and receive real-time data from those systems as inputs. To convert signals and ensure that the temporal sequences and magnitudes reflect laboratory settings, the ability to scale and project data is essential. To demonstrate this ability, Dynamical System Scaling (DSS) and Hierarchical Two-Tiered Scaling (H2TS) (methodologies that enable systems to scale and project or extrapolate data sets to desired environments while conserving the observed behavior based on first principles) were applied to DETAIL’s thermocline thermal storage system in the Thermal Energy Distribution System (TEDS) facility and solid-oxide electrolysis cell in the High Temperature Hydrogen Electrolysis (HTHE) facility. Both thermocline and electrolysis cell systems were successfully scaled, and test cases were conducted to generate a doubly accelerated energy charge and discharge in reference to past experimental data from the facilities. The research results represented a case for the thermocline system that required signals to be accelerated without altering the stored energy. To enhance the quality of the accelerated data, error propagation analyses were conducted on DSS post-processing terms to determine the consequences of raw-data-associated errors.

08 HYDROGEN↗
DOE OSTI2021

Model America - data and models of every U.S. building

The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

Detection of nighttime atmospheric scattering of lunar UV radiances by the Nimbus 4 BUV instrument

Morphological studies of nighttime dark current data from the Nimbus 4 backscattered UV experiment indicate enhancements during the period of a full moon. The nature and magnitude of these lunar UV radiance enhancements are determined, and their potential use as a measure of nighttime ozone is considered. The data were grouped into five-day study intervals centered about each full moon sequence, and about each corresponding new moon interval. The analysis was performed in a magnetic frame of reference (McIlwain, 1961) in order to evaluate magnetospheric perturbation effects and to minimize the effects of charged energetic particle contamination or precipitation. All isolated elements showing spurious or abnormal enhancements were removed selectively (about 3%) to further screen the data. Results demonstrate the presence and uniqueness of a lunar signal, induced by atmospherically backscattered UV radiation. This signal was not sufficiently strong, however, to accurately map global nighttime ozone on the Nimbus 4 instrument.

Stassinopoulos, E. G.↗
NASA NTRS1986

Utility of remotely sensed data for identification of soil conservation practices

Discussed are a variety of remotely sensed data sources that may have utility in the identification of conservation practices and related linear features. Test sites were evaluated in Alabama, Kansas, Mississippi, and Oklahoma using one or more of a variety of remotely sensed data sources, including color infrared photography (CIR), LANDSAT Thematic Mapper (TM) data, and aircraft-acquired Thermal Infrared Multispectral Scanner (TIMS) data. Both visual examination and computer-implemented enhancement procedures were used to identify conservation practices and other linear features. For the Kansas, Mississippi, and Oklahoma test sites, photo interpretations of CIR identified up to 24 of the 109 conservation practices from a matrix derived from the SCS National Handbook of Conservation Practices. The conservation practice matrix was modified to predict the possibility of identifying the 109 practices at various photographic scales based on the observed results as well as photo interpreter experience. Some practices were successfully identified in TM data through visual identification, but a number of existing practices were of such size and shape that the resolution of the TM could not detect them accurately. A series of computer-automated decorrelation and filtering procedures served to enhance the conservation practices in TM data with only fair success. However, features such as field boundaries, roads, water bodies, and the Urban/Ag interface were easily differentiated. Similar enhancement techniques applied to 5 and 10 meter TIMS data proved much more useful in delineating terraces, grass waterways, and drainage ditches as well as the features mentioned above, due partly to improved resolution and partly to thermally influenced moisture conditions. Spatially oriented data such as those derived from remotely sensed data offer some promise in the inventory and monitoring of conservation practices as well as in supplying parameter data for a variety of computer-implemented agricultural models.

Pelletier, R. E.↗
NASA NTRS2019

Creating Data-Driven Vector Visualizations of Satellite Orbit Tracks Using NASA GIBS and Worldview

NASA Earth Observing System (EOS) currently operates dozens of remote sensing satellites, many of which can be viewed directly in NASA’s open-source Worldview application. Much of this satellite imagery can be viewed in near-real time as it is processed and served by NASA’s Global Imagery Browse Service (GIBS). To better educate users on the time and location of imagery, GIBS serves orbit track specific layers for each satellite. Worldview has historically served these layers as raster images but recent updates have enabled the application to now serve these layers using vector tiles. With the release of Worldview v3.0, orbit track layers can be displayed using mapbox vector tiles (MVT). This visualization format allows users to not only view and change the color of orbit track layers, as they could do previously with rasters, but also inspect individual vector points and filter layers by specific parameters such as time. The data contained within a MVT is further enhanced in Worldview with the combination of a JSON description file served from GIBS used to describe the MVT data. This presentation will provide an overview of the process of consuming orbit track vector tiles and data files from GIBS using a pipeline to configure, build and ultimately display the orbit tracks in Worldview. Furthermore, the presentation aims to describe how others can leverage our open-source code to display and enhance vector layers in their own applications.

Rice, Zachary↗
NASA NTRS1984

The role of optimization in structural model refinement

To evaluate the role that optimization can play in structural model refinement, it is necessary to examine the existing environment for the structural design/structural modification process. The traditional approach to design, analysis, and modification is illustrated. Typically, a cyclical path is followed in evaluating and refining a structural system, with parallel paths existing between the real system and the analytical model of the system. The major failing of the existing approach is the rather weak link of communication between the cycle for the real system and the cycle for the analytical model. Only at the expense of much human effort can data sharing and comparative evaluation be enhanced for the two parallel cycles. Much of the difficulty can be traced to the lack of a user-friendly, rapidly reconfigurable engineering software environment for facilitating data and information exchange. Until this type of software environment becomes readily available to the majority of the engineering community, the role of optimization will not be able to reach its full potential and engineering productivity will continue to suffer. A key issue in current engineering design, analysis, and test is the definition and development of an integrated engineering software support capability. The data and solution flow for this type of integrated engineering analysis/refinement system is shown.

Lehman, L. L.↗
DOE OSTI2024

Carbon Storage Technical Viability Approach and National Data Assessment

Carbon Storage Technical Viability Approach is a comprehensive evaluation of potential geologic carbon storage sites that includes classic subsurface resource assessment components such as reservoir suitability in addition to hazard, environmental, social, regulatory, and jurisdiction components that may enhance or hinder successful carbon storage. Data for assessments of technically viable carbon storage span many categories, types; are disparate and numerous. Variables and types of data required to support CS assessments were previously not clearly defined and documented. Contextualizing available data indicates their utility, potential uncertainty, and gaps. This presentation details the Carbon Storage Technical Viability Approach, the associated matrix and database, and initial results from a portion of the national data availability assessment that contextualizes the data available to support carbon storage projects. Presented at the American Association of Petroleum Geologists' Carbon Capture Utilization and Storage (SPE-AAPG-SEG CCUS 2024) conference in Houston, TX, March 11-13, 2024.

Mark-Moser, Mackenzie K.↗
DOE OSTI2022

Brownian bridge-based speed imputation technique for truck energy consumption and emissions estimation

The available truck Global Positioning System (GPS) data, typically collected with large time gaps, rely on imputation techniques to obtain second-by-second data that are required in models for estimating truck energy consumption and emissions. However, existing speed imputation techniques either require a large amount of high-resolution data for model training or rely on special movement assumptions. Here, to fill the gap and effectively apply the low-resolution truck GPS datasets, this paper proposes a simple imputation technique that adopts the Brownian bridge structure to impute missing speed data. The proposed technique introduces a feasible imputation region and a combined drift into the imputation procedure to capture vehicle acceleration constraint, travel distance constraint, and speed volatility. The calibrated model is applied to a set of low-resolution truck GPS data. The results demonstrate the robustness of the proposed technique in enhancing estimation accuracy when using low-resolution GPS data to estimate fuel consumption and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗