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At least 289 records · Page 16

Urban Air Quality Management at Low-Cost Using Micro Air Sensors: A Case Study From Accra, Ghana

Urban air quality management is dependent on the availability of local air pollution data. In many major urban centers of Africa, there is limited to non-existent information on air quality. This is gradually changing in part due to the increasing use of micro air sensors which have the potential to enable the generation of ground-based air quality data at fine scales for understanding local emission trends. Regional literature on the application of the high-resolution data for emission source identification in this region is limited. In this study a micro air sensor was co-located at the Physics Department, University of Ghana with a reference grade instrument to evaluate its performance for estimating PM2.5 pollution accurately at fine scales and the value of this data in identification of local sources and their behavior over time. For this study 15 weeks of data at hourly resolution with approximately 2500 data pairs are generated and analyzed (June 01, 2023, to September 15, 2023). For this time period a coefficient of determination (r 2 ) of 0.83 was generated with a mean absolute error (MAE) of 5.44 μgm -3 between the pre local calibration micro air sensor (i.e. out of box) and the reference-grade instrument. Following currently accepted best practice methods (see e.g., PAS4023) a domain specific (i.e. local) calibration factor was generated using a multi-linear regression model and when this factor is applied to the micro air sensor data, a reduction i.e., improvement in MAE to 1.43 μgm -3 was found. Daily variation was calculated, a receptor model was applied, and time series plots as a function of wind direction were generated, including PM2.5/PM10 ratio scatter and count plots to explore the utility of this observational approach for local source identification. The 3 data sets were compared (out of box, domain calibrated and reference-grade) and it was found that although there were variations in the data reported, source areas highlighted based on these data were similar, with input from local sources such as traffic emissions and biomass burning. As the temporal resolution of observational data associated with these micro air sensors is higher than for reference grade instruments (primarily due to costs and logistics limitations), they have the potential to provide insight into the complex, often hyper localized sources associated with urban areas, such as those found in major African cities.

Source apportionment↗

Classification results using spacially correlated Landsat data

Tubbs and Coberly (1978) demonstrated that Landsat multispectral scanner data are not independent random observations, but, are in fact highly correlated. They also demonstrated that the correlation structure for the data is similar to that of a stationary autoregressive process of order one. This paper investigates the effect that serially correlated training data have upon both the estimation of parameters and the classification problem. Results are included for both the Bayesian and maximum likelihood classification procedures.

Tubbs, J. D.↗

Development and testing of dry chemicals in advanced extinguishing systems for jet engine nacelle fires

The effectiveness of dry chemical in extinguishing and delaying reignition of fires resulting from hydrocarbon fuel leaking onto heated surfaces such as can occur in jet engine nacelles is studied. The commercial fire extinguishant dry chemical tried are sodium and potassium bicarbonate, carbonate, chloride, carbamate (Monnex), metal halogen, and metal hydroxycarbonate compounds. Synthetic and preparative procedures for new materials developed, a new concept of fire control by dry chemical agents, descriptions of experiment assemblages to test dry chemical fire extinguishant efficiencies in controlling fuel fires initiated by hot surfaces, comparative testing data for more than 25 chemical systems in a 'static' assemblage with no air flow across the heated surface, and similar comparative data for more than ten compounds in a dynamic system with air flows up to 350 ft/sec are presented.

Altman, R. L.↗

A Long-Term Merged Global Ozone Data Set

Using data from a series of space-based ozone measurement systems we are producing a consistent, calibrated ozone time series that can be used for trend analyses and other studies. To produce the total column ozone time series we use data from Total Ozone Mapping Spectrometer (TOMS) instruments on Nimbus 7 and Earth Probe, and data from the Ozone Monitoring Instrument (OMI) flying on the Aura spacecraft. Both total column ozone and the ozone vertical profile data are produced from the Solar Backscatter Ultraviolet (SBUV) instruments on Nimbus 7 and SBUV/2 instruments on a series of NOAA spacecraft. A global zonal mean merged ozone data time series covering the period from 1970-1972 and 1978-2010 has been produced for total column ozone. A similar profile data set has been constructed, but is still in preliminary form due to uncertainty in calibration adjustments as a function of latitude and altitude.

McPeters, Richard D.↗

Solar-System Tests of Gravitational Theories

We are engaged in testing gravitational theory by means of observations of objects in the solar system. These tests include an examination of the Principle Of Equivalence (POE), the Shapiro delay, the advances of planetary perihelia, the possibility of a secular variation G in the "gravitational constant" G, and the rate of the de Sitter (geodetic) precession of the Earth-Moon system. These results are consistent with our preliminary results focusing on the contribution of Lunar Laser Ranging (LLR), which were presented at the seventh Marcel Grossmann meeting on general relativity. The largest improvement over previous results comes in the uncertainty for (eta): a factor of five better than our previous value. This improvement reflects the increasing strength of the LLR data. A similar analysis presented at the same meeting by a group at the Jet Propulsion Laboratory gave a similar result for (eta). Our value for (beta) represents our first such result determined simultaneously with the solar quadrupole moment from the dynamical data set. These results are being prepared for publication. We have shown how positions determined from different planetary ephemerides can be compared and how the combination of VLBI and pulse timing information can yield a direct tie between planetary and radio frames. We have continued to include new data in our analysis as they became available. Finally, we have made improvement in our analysis software (PEP) and ported it to a network of modern workstations from its former home on a "mainframe" computer.

Shapiro, Irwin↗

First spatio-temporal results from the LDEF Interplanetary Dust Experiment

The LDEF Interplanetary Dust Experiment is unique in providing a time history of impacts of micron-sized particles on six orthogonal faces of the vehicle over a span of nearly a full year. Over 15,000 hits were recorded, representing a mix of zodiacal dust, meteor-stream grains, orbital debris, perhaps beta-meteoroids, and possibly interstellar matter. Although the total number was higher than predicted, the relative panel activity distribution was near expectations. Detailed deconvolution of the impact record with orbital data is underway, to examine each of these populations. Very preliminary results of the fairly crude 'first-look' analysis suggest that debris is the major particle component at 500 km. The data show clear evidence of some known meteor streams as sharp, tightly-focused events, unlike their visible counterparts. Some apparent debris events show similar signatures. Data from the leading and trailing edges suggest a detection of beta-meteoroids, but the analysis is not yet conclusive. Absolute fluxes and flux ratios are not yet known, since the detector status analysis is yet incomplete.

Singer, S. F.↗

Hover and forward flight acoustics and performance of a small-scale helicopter rotor system

A 2.1-m diam., 1/6-scale model helicopter main rotor was tested in hover in the test section of the NASA Ames 40- by 80- Foot Wind Tunnel. Subsequently, it was tested in forward flight in the Ames 7- by 10-Foot Wind Tunnel. The primary objective of the tests was to obtain performance and noise data on a small-scale rotor at various thrust coefficients, tip Mach numbers, and, in the later case, various advance ratios, for comparisons with similar existing data on full-scale helicopter rotors. This comparison yielded a preliminary evaluation of the scaling of helicopter rotor performance and acoustic radiation in hover and in forward flight. Correlation between model-scale and full-scale performance and acoustics was quite good in hover. In forward flight, however, there were significant differences in both performance and acoustic characteristics. A secondary objective was to contribute to a data base that will permit the estimation of facility effects on acoustic testing.

Kitaplioglu, C.↗

Geophysical Retrievals and Cloud Analyses from Merged Airborne Radiometer Datasets Covering 10–684 GHz

Airborne microwave radiometers provide insight about numerous aspects of Earth’s atmosphere and yield critical validation datasets for spaceborne radiometers. Three radiometers that are important to NASA’s airborne remote-sensing arsenal include: the Advanced Microwave Precipitation Radiometer (AMPR), covering 10–85 GHz; the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR), covering 50–183 GHz; and the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR), covering 170–684 GHz. The NASA field campaigns of interest to this study include: the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014, the Olympic Mountains Experiment and Radar Definition Experiment (OLYMPEX/RADEX) in 2015–2016, the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) in 2020–2023, and the Airborne Lightning Observatory for FEGS and TGFs (ALOFT) in 2023. To provide a more comprehensive perspective on clouds and precipitation observed during these airborne field campaigns, AMPR data were merged spatiotemporally with CoSMIR data for IPHEx, OLYMPEX/RADEX, and IMPACTS (2020 and 2022), while considering differences in instrument characteristics and operations, providing brightness temperature (Tb) values from 10–183 GHz in a common background grid throughout each flight. AMPR and CoSSIR data were similarly merged for IMPACTS (2023) and ALOFT, providing a common background grid with Tb values covering 10–684 GHz throughout each flight. These merged Tb data were employed in geophysical retrievals using the Community Radiative Transfer Model (CRTM), an Eddington radiative transfer model, and a one-dimensional variational (1DVAR) inversion method. Retrievals of cloud liquid water path were of primary interest. This presentation will include an overview of the methods for the radiometer data mergers, the radiative transfer methods, the geophysical retrievals, and detailed results from examining trends in Tb and cloud liquid water path in clouds, precipitation, and cloud-to-precipitation transition zones.

Corey G Amiot↗

The Penn State ORSER system for processing and analyzing ERTS data

The Office for Remote Sensing of Earth Resources (ORSER) of the Space Science and Engineering Laboratory (SSEL) at The Pennsylvania State University has developed an extensive operational system for processing and analyzing ERTS-1 and similar multispectral data. Specific results obtained by using this system include a study of land use, discrimination between types of forest resources and vegetation, detection of previously unknown geologic faults and correlation of these with known mineral deposits and ground water, mapping of mine spoils in the anthracite region of eastern Pennsylvania, mapping of strip mines and acid mine drainage in Central Pennsylvania, agricultural land use mapping, and detection of gypsy moth infestation.

Mcmurtry, G. J.↗

The Penn State ORSER system for processing and analyzing ERTS and other MSS data

The Office for Remote Sensing of Earth Resources (ORSER) of the Space Science and Engineering Laboratory (SSEL) at the Pennsylvania State University has developed an extensive operational system for processing and analyzing ERTS-1 and similar multispectral data. The ORSER system was developed for use by a wide variety of researchers working in remote sensing. Both photointerpretive techniques and automatic computer processing methods have been developed and used, separately and in a combined approach. A Remote Job Entry (RJE) system permits use of an IBM 370/168 computer from any compatible remote terminal, including equipment tied in by long-distance telephone connections. An elementary cost analysis has been prepared for the processing of ERTS data.

Mcmurtry, G. J.↗

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗

High-Latitude Topside Ionospheric Vertical Electron-Density-Profile Changes in Response to Large Magnetic Storms

Large magnetic-storm induced changes have been detected in high-latitude topside vertical electron-density profiles Ne(h). The investigation was based on the large database of topside Ne(h) profiles and digital topside ionograms from the International Satellites for Ionospheric Studies (ISIS) program available from the NASA Space Physics Data Facility (SPDF) at http://spdf.gsfc.nasa.gov/isis/isis-status.html. This large database enabled Ne(h) profiles to be obtained when an ISIS satellite passed through nearly the same region of space before, during, and after a major magnetic storm. A major goal was to relate the magnetic-storm induced high-latitude Ne(h) profile changes to solar-wind parameters. Thus an additional data constraint was to consider only storms where solar-wind data were available from the NASA/SPDF OMNIWeb database. Ten large magnetic storms (with Dst less than -100 nT) were identified that satisfied both the Ne(h) profile and the solar-wind data constraints. During five of these storms topside ionospheric Ne(h) profiles were available in the high-latitude northern hemisphere and during the other five storms similar ionospheric data were available in the southern hemisphere. Large Ne(h) changes were observed during each one of these storms. Our concentration in this paper is on the northern hemisphere. The data coverage was best for the northern-hemisphere winter. Here Ne(h) profile enhancements were always observed when the magnetic local time (MLT) was between 00 and 03 and Ne(h) profile depletions were always observed between 08 and 10 MLT. The observed Ne(h) deviations were compared with solar-wind parameters, with appropriate time shifts, for four storms.

solar wind↗

Adaptations of human skeletal muscle fibers to spaceflight

Human skeletal muscle fibers seem to share most of the same interrelationships among myosin ATPase activity, myosin heavy chain (MHC) phenotype, mitochondrial enzyme activities, glycolytic enzyme activities, and cross-sectional area (CSA) as found in rat, cat, and other species. One difference seems to be that fast fibers with high mitochrondrial content occur less frequently in humans than in the rat or cat. Recently, we have reported that the type of MHC expressed and the size of the muscle fibers in humans that have spent 11 days in space change significantly. Specifically, about 8% more fibers express fast MHCs and all phenotypes atrophy in the vastus lateralis (VL) post compared to preflight. In the present paper we examine the relationships among the population of myonuclei, MHC type, and CSA of single human muscle fibers before and after spaceflight. These are the first data that define the relationship among the types of MHC expressed, myonuclei number, and myonuclei domain of single fibers in human muscle. We then compare these data to similar measures in the cat. In addition, the maximal torque that can be generated by the knee extensors and their fatigability before and after spaceflight are examined. These data provide some indication of the potential physiologica consequences of the muscle adaptations that occur in humans in response to spaceflight.

M. Kathleen Day↗

Method for Real-Time State Estimation of Structural Modes for an Aeroelastic Wind Tunnel Model

A method for estimating displacements, velocities, and accelerations of structural modes in generalized coordinates from measured sensor data in real time is developed and demonstrated. Data from conventional strain gauges and fiber optic strain sensors (FOSS) were combined with strain mode shapes to produce least-squares estimates of the structural mode displacements. Similarly, accelerometer data were combined with displacement mode shapes to estimate structural mode accelerations. Estimates were then combined using a Kalman filter to refine the displacement estimates and produce structural mode velocity estimates. The approach was demonstrated using simulation data for the NASA-Boeing collaboration called the Integrated Adaptive Wing Technology Maturation (IAWTM) project in both a stable open-loop condition and an unstable condition where estimated displacement and velocity states were used for feedback control. Results supported the feasibility of using this approach for feedback control and system identification applications for wind tunnel tests.

Aeroservoelasticity↗

Correlation Filtering of Modal Dynamics using the Laplace Wavelet

Wavelet analysis allows processing of transient response data commonly encountered in vibration health monitoring tasks such as aircraft flutter testing. The Laplace wavelet is formulated as an impulse response of a single mode system to be similar to data features commonly encountered in these health monitoring tasks. A correlation filtering approach is introduced using the Laplace wavelet to decompose a signal into impulse responses of single mode subsystems. Applications using responses from flutter testing of aeroelastic systems demonstrate modal parameters and stability estimates can be estimated by correlation filtering free decay data with a set of Laplace wavelets.

Freudinger, Lawrence C.↗

Development of a Computer Architecture to Support the Optical Plume Anomaly Detection (OPAD) System

The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts spectral information from the engine plume and reports the amounts of metals which are present in the plume. The development of this software is at a sufficiently advanced stage where it can be used in actual engine tests to provide valuable data on engine operation and health. This activity will continue and, in addition, the OPAD system is planned to be used in flight aboard space vehicles. The two implementations, test-stand and in-flight, may have some differing requirements. For example, the data stored during a test-stand experiment are much more extensive than in the in-flight case. In both cases though, the majority of the requirements are similar. New data from the spectrograph is generated at a rate of once every 0.5 sec or faster. All processing must be completed within this period of time to maintain real-time performance. Every 0.5 sec, the OPAD system must report the amounts of specific metals within the engine plume, given the spectral data. At present, the software in the OPAD system performs this function by solving the inverse problem. It uses powerful physics-based computational models (the SPECTRA code), which receive amounts of metals as inputs to produce the spectral data that would have been observed, had the same metal amounts been present in the engine plume. During the experiment, for every spectrum that is observed, an initial approximation is performed using neural networks to establish an initial metal composition which approximates as accurately as possible the real one. Then, using optimization techniques, the SPECTRA code is repetitively used to produce a fit to the data, by adjusting the metal input amounts until the produced spectrum matches the observed one to within a given level of tolerance. This iterative solution to the original problem of determining the metal composition in the plume requires a relatively long period of time to execute the software in a modern single-processor workstation, and therefore real-time operation is currently not possible. A different number of iterations may be required to perform spectral data fitting per spectral sample. Yet, the OPAD system must be designed to maintain real-time performance in all cases. Although faster single-processor workstations are available for execution of the fitting and SPECTRA software, this option is unattractive due to the excessive cost associated with very fast workstations and also due to the fact that such hardware is not easily expandable to accommodate future versions of the software which may require more processing power. Initial research has already demonstrated that the OPAD software can take advantage of a parallel computer architecture to achieve the necessary speedup. Current work has improved the software by converting it into a form which is easily parallelizable. Timing experiments have been performed to establish the computational complexity and execution speed of major components of the software. This work provides the foundation of future work which will create a fully parallel version of the software executing in a shared-memory multiprocessor system.

Katsinis, Constantine↗

Autocorrelation in Landsat data

Many computer algorithms for the analysis of Landsat data have a statistical basis which requires that the observations comprise independent samples. Four distinct methods are employed to show that this assumption commonly is not fulfilled for these data. Each leads to a similar conclusion; the data must be sampled no closer than every 10th pixel in order to yield independent estimators. The implications of this are illustrated with a simple example.

Craig, R. G.↗

Accessing and Visualizing scientific spatiotemporal data

This paper discusses work done by JPL 's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids These tools do one or more of the following tasks visualize local data sets for local users, visualize local data sets for remote users, and access and visualize remote data sets The tools are used for various types of data, including remotely sensed image data, digital elevation models, astronomical surveys, etc The paper attempts to pull some common elements out of these tools that may be useful for others who have to work with similarly large data sets.

data sets↗