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At least 181 records · Page 10

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors Mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗

Fit2Fly Project

NASA’s Fit2Fly project wants to make future commercial drone fleet operations routine, safe, and boring. How can future operators of commercial drone fleets know without a doubt that their aircraft are fit to fly? It is a tough problem, because every flight will effectively break the chain of custody for their aircraft, and having technicians do detailed inspections after each flight is not viable for large, busy fleets.

airworthiness↗

Simulator evaluation of displays for a revised takeoff performance monitoring system

Cockpit displays for a Takeoff Performance Monitoring System (TOPMS) to provide pilots with graphic and alphanumeric information pertinent to their decision to continue or abort a takeoff are evaluated. Revised head-down and newly developed head-up displays were implemented on electronic screens in the real-time Transport Systems Research Vehicle (TSRV) Simulator for the Boeing 737 airplane at the Langley Research Center and evaluated by 17 NASA, U.S. Air Force, airline, and industry pilots. Both types of displays were in color, but they were not dependent upon it. The TOPMS head-down display is composed of a runway graphic overlaid with symbolic status and advisory information related to both the expected takeoff point and the predicted stop point (in the event an abort becomes necessary). In addition, an overall Situation Advisory Flag indicates a preferred course of action based on analysis of the various elements of airplane performance and system status. A simpler head-up display conveys most of this same information and relates it to the visual scene. The evaluation pilots found the displays to be credible, easy to monitor, and appropriate for the task. In particular, the pilots said the head-up display was monitored with very little effort and did not obstruct or distract them from monitoring the simulated out-the-window runway scene. This report augments NASA TP-2908, 1989.

Middleton, David B.↗

The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present and Future

The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.

Aerosol↗

AviSense: A Real-time System for Detection, Classification, and Analysis of Aviation Signals

Wireless systems are an integral part of aviation. Apart from their apparent use in air-to-ground communication, wireless systems play a crucial role in avionic functions including navigation and landing. An interference-free wireless environment is therefore critical for the uninterrupted operation and safety of an aircraft. Hence, there is an urgency for airport facilities to acquire the capability to continuously monitor aviation frequency bands for real-time detection of interference and anomalies. To meet this critical need, we design and build AviSense, an SDR-based real-time, versatile system for monitoring aviation bands. AviSense detects and characterizes signal activities to enable practical and effective anomaly detection. We identify and tackle the challenges posed by a diverse set of critical aviation bands and technologies. We evaluate our methodology with real-world aviation signal measurements and two custom datasets of anomalous signals. We find that our signal classification capability achieves a true positive rate of ~99%, with few exceptions, and a false positive rate of less than 4%. We also demonstrate that AviSense can effectively distinguish between different types of anomalies. We build and evaluate a prototype implementation of AviSense that supports distributed monitoring.

42 ENGINEERING↗

Southern Idaho Health & Air Quality: Monitoring Atmospheric Mixing Heights Post-Wildfire Through the Use of NASA Earth Observations

Wildfire smoke has long-lasting impacts on public and environmental health. Currently, agencies that monitor smoke base their decisions on an analysis of how fires burn, the direction the smoke moves from the fire source, and unverified estimates of mixing height. Mixing heights describe the maximum altitude to which a smoke plume rises. Satellite imagery provides more continuous and accurate coverage of mixing heights than current in situ methods. Thus, the team developed a software tool that processes and extracts mixing height observations from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Vertical Feature Mask granules. The team partnered with the National Oceanic and Atmospheric Administration’s National Weather Service, the Bureau of Land Management’s National Interagency Fire Center, and the National Park Service’s Fire Management Program Center to analyze historic fire events in southern Idaho. To do so, they used Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to verify where a CALIPSO pass intersects thermal anomalies and smoke plumes. The software extracts features of relevance from the hdf file of each CALIPSO transect to locate layers of continuous aerosols. The maximum altitude at which the aerosol ends is recorded as the mixing height, along with a matching latitude and longitude. The satellite-derived values can be used to validate past mixing height predictions and evaluate the accuracy and systematic bias of different estimation methods. These results may allow agencies to make better comparisons and subsequent smoke pollution management, prevention, and public health decisions if the spatial and temporal differences between predictions and observations can be resolved.

DEVELOP Project Summary↗

Challenges in the study of chemistry and photochemistry at air–water interfaces: Toward in situ monitoring of reaction kinetics with spectroscopic techniques

Air–water interfaces, including those on droplet surfaces, have been the subject of many recent experiments due to their propensity for unique chemistry. Here, in this study, an overview of some recent advancements in understanding interfacial reaction kinetics is provided, highlighting non-surface-specific methods—such as mass spectrometry—compared with the advantages of surface-specific techniques—such as reflection–absorption spectroscopy, sum frequency generation, and photoelectron spectroscopy. This Perspective discusses the information depth and time constraints of common surface-specific spectroscopic methods that need to be addressed to monitor interfacial chemistry in situ and uses a few key examples from the literature as case studies. It concludes by advocating for the continued development of advanced spectroscopic methods to further investigate interfacial chemistry, underscoring the need for interdisciplinary collaboration to bridge the gap between molecular-level insights and macroscopic observations in future research.

Air-water interface↗

New Approach to Monitor Transboundary Particulate Pollution over Northeast Asia

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched.

Data Assimilation↗

Lessons Learned from Demolition of Hanford's Plutonium Finishing Plant - 20507

U.S. Department of Energy (DOE) contractor CH2M Hill Plateau Remediation Company (CHPRC), a Jacobs owned company, is making significant progress demolishing the Plutonium Finishing Plant (PFP), which has long been known as one of the most hazardous buildings in the DOE Environmental Management Complex (DOE Complex). The facility is located on the Hanford Site and produced plutonium metal during the Cold War. Production was stopped in 1989, the facility was formally shut down in 1996, and material processing was completed in 2004. After approximately 25 years of demolition preparations, open-air demolition of the main portions of the Hazard Category II nuclear facility began in November 2016. To prepare the PFP for demolition, CHPRC employees performed some of the most hazardous work across the DOE Complex. In addition to extensive demolition preparations, including a wide-reaching communication strategy across the Hanford Site, CHPRC implemented robust controls and monitoring during demolition, and when necessary, adjusted demolition practices and sequence to maintain employee safety and project efficiency. Demolition of the main PFP building began in November 2016. The technical complexity, high hazards and radiological concerns have all led to a difficult demolition environment. Following a spread of contamination at the project site beyond the radiological boundaries in December 2017, work was halted and a recovery plan was generated to allow the demolition work to continue. After the implementation of additional controls and concurrence from regulatory agencies and DOE, the demolition was ready to resume work and reinitiated in August 2018. There are a number of lessons learned from the demolition activities and recovery plan process. This paper allows CHPRC and DoE's Richland Operations Office (RL) to share lessons learned and progress to date with other challenging and hazardous projects across the DOE Complex. Understanding the risk acceptance level is critical to execution of any open-air demolition project and is unique to each facility. Four key lessons learned from this project include: 1) plan execution issues, 2) stakeholder communication issues, 3) watching for summit fever and 4) minimizing exposed contaminated surfaces during demolition. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Global Land-Ocean Temperature Index in Relation to Sunspot Number, the Atlantic Multidecadal Oscillation Index, the Mauna Loa Atmospheric Concentration of CO2, and Anthropogenic Carbon Emissions

Global warming/climate change has been a subject of scientific interest since the early 19th century. In particular, increases in the atmospheric concentration of carbon dioxide (CO2) have long been thought to account for Earth's increased warming, although the lack of a dependable set of observational data was apparent as late as the mid 1950s. However, beginning in the late 1950s, being associated with the International Geophysical Year, the opportunity arose to begin accurate continuous monitoring of the Earth's atmospheric concentration of CO2. Consequently, it is now well established that the atmospheric concentration of CO2, while varying seasonally within any particular year, has steadily increased over time. Associated with this rising trend in the atmospheric concentration of CO2 is a rising trend in the surface-air and sea-surface temperatures (SSTs). This Technical Publication (TP) examines the statistical relationships between 10-year moving averages (10-yma) of the Global Land-Ocean Temperature Index (GLOTI), sunspot number (SSN), the Atlantic Multidecadal Oscillation (AMO) index, and the Mauna Loa CO2 (MLCO2) index for the common interval 1964-2006, where the 10-yma values are used to indicate trends in the data. Scatter plots using the 10-yma values between GLOTI and each of the other parameters are determined, both as single-variate and multivariate fits. Scatter plots are also determined for MLCO2 using single-variate and bivariate (BV) fits, based on the GLOTI alone and the GLOTI in combination with the AMO index. On the basis of the inferred preferential fits for MLCO2, estimates for MLCO2 are determined for the interval 1885-1964, thereby yielding an estimate of the preindustrial level of atmospheric concentration of CO2. Lastly, 10-yma values of MLCO2 are compared against 10-yma estimates of the total carbon emissions (TCE) to determine the likelihood that manmade sources of carbon emissions are indeed responsible for the recent warming now being experienced. (Parametric values used in this TP are those available prior to the end of 2012.)

Wilson, Robert M.↗

Continuous measurement of aircraft wing icing

Ice formation on the wings of aircraft is a problem that has plagued air travel since its inception. Several recent incidents have been attributed to ice formation on the lifting surfaces of wings. This paper describes a SBIR Phase 1 research effort on the use of small flat dielectric sensors in detecting a layer of ice above the sensor. The sensors are very small, lightweight, and inexpensive. The electronics package that controls the sensor is also small, and could be even smaller using commonly available miniaturization technologies. Thus, several sensors could be placed on a surface such that a representative ice thickness profile could be measured. The benefits offered by developing this technology go beyond the safety improvements realized by monitoring ice formation on the wings of an aircraft. Continuous monitoring of anti-icing fluid concentrations on the ground would warn the pilot of impending fluid failure as well as allowing the stations to use less de-icing solution per aircraft. This in turn would increase the safety of takeoffs and reduce the overall discharge of de-icing solution into the environment, thus reducing the biohazard of the de-icing procedure.

Yao, Stephen S. C.↗

Subcritical crack growth of selected aerospace pressure vessel materials

This experimental program was undertaken to determine the effects of combined cyclic/sustained loads, stress level, and crack shape on the fatigue crack growth rate behavior of cracks subjected to plane strain conditions. Material/environment combinations tested included: 2219-T87 aluminum plate in gaseous helium, room air, and 3.5% NaCl solution at room temperature, liquid nitrogen, and liquid hydrogen; 5Al-2.5 Sn (ELI) titanium plate in liquid nitrogen and liquid hydrogen and 6AL-4V (ELI) STA titanium plate in gaseous helium and methanol at room temperature. Most testing was accomplished using surface flawed specimens instrumented with a clip gage to continuously monitor crack opening displacements at the specimen surface. Tapered double cantilever beam specimens were also tested. Static fracture and ten hour sustained load tests were conducted to determine fracture toughness and apparent threshold stress intensity values. Cyclic tests were performed using sinusoidal loading profiles at 333 MHz (20 cpm) and trapezoidal loading profiles at both 8.3 MHz (0.5 cpm) and 3.3 MHz (0.2 cpm). Data were evaluated using modified linear elastic fracture mechanics parameters.

Hall, L. R.↗

Tools and Data Services from the GSFC Earth Sciences DAAC for Aura Science Data Users

In these times of rapidly increasing amounts of archived data, tools and data services that manipulate data and uncover nuggets of information that potentially lead to scientific discovery are becoming more and more essential. The Goddard Space Flight Center (GSFC) Earth Sciences (GES) Distributed Active Archive Center (DAAC) has made great strides in facilitating science and applications research by, in consultation with its users, developing innovative tools and data services. That is, as data users become more sophisticated in their research and more savvy with information extraction methodologies, the GES DAAC has been responsive to this evolution. This presentation addresses the tools and data services available and under study at the GES DAAC, applied to the Earth sciences atmospheric data. Now, with the data from NASA's latest Atmospheric Chemistry mission, Aura, being readied for public release, GES DAAC tools, proven successful for past atmospheric science missions such as MODIS, AIRS, TRMM, TOMS, and UARS, provide an excellent basis for similar tools updated for the data from the Aura instruments. GES DAAC resident Aura data sets are from the Microwave Limb Sounder (MLS), Ozone Monitoring Instrument (OMI), and High Resolution Dynamics Limb Sounder (HIRDLS). Data obtained by these instruments afford researchers the opportunity to acquire accurate and continuous visualization and analysis, customized for Aura data, will facilitate the use and increase the usefulness of the new data. The Aura data, together with other heritage data at the GES DAAC, can potentially provide a long time series of data. GES DAAC tools will be discussed, as well as the GES DAAC Near Archive Data Mining (NADM) environment, the GIOVANNI on-line analysis tool, and rich data search and order services. Information can be found at: http://daac.gsfc.nasa.gov/upperatm/aura/. Additional information is contained in the original extended abstract.

Kempler, S.↗

Long term monitoring of methane in the atmosphere by multiplex gas chromatography

Methane is of interest in the study of the Earth's atmosphere because of its implication in the future global warming of the surface. This warming is produced by the absorption of infrared energy by trace gases. It has been estimated that in the next 40 to 50 years, methane could contribute 20 to 25 pct. as much atmospheric warming as that expected from carbon dioxide increases. Studies to examine sources, sinks, and cycles of methane will require analytical methods capable of continuous unattended measurement with temporal resolution of an hour or less for weeks at a time. Gas chromatography (GC) is one of the most practical methods available to conduct the analysis of air, but limitations in this technique still exist which can be alleviated with multiplex GC (MGC). MGC is a technique where many samples are pseudo-randomly introduced to the chromatograph without regard to the length of time required for an analysis. The resulting data must then be reduced using computational methods such as cross correlation. In the technique reported, a tube packed with silver oxide was used at the inlet of the GC column to create concentration pulses of methane in a sample stream of air. By using only one carrier, i.e., ambient air, an effective and accurate method to monitor the variations in concentration of methane in the atmosphere over long periods of time was developed. Methane in ambient air was monitored for an eight day period and an interesting temporal variability was found. This work has shown the utility of a relatively simple MGC for the analysis of a real environmental sample.

Valentin, Jose R.↗

Ozone Monitoring Instrument Observations of Interannual Increases in SO2 Emissions from Indian Coal-fired Power Plants During 2005-2012

Due to the rapid growth of electricity demand and the absence of regulations, sulfur dioxide (SO2) emissions from coal-fired power plants in India have increased notably in the past decade. In this study, we present the first interannual comparison of SO2 emissions and the satellite SO2 observations from the Ozone Monitoring Instrument (OMI) for Indian coal-fired power plants during the OMI era of 2005-2012. A detailed unit-based inventory is developed for the Indian coal-fired power sector, and results show that its SO2 emissions increased dramatically by 71 percent during 2005-2012. Using the oversampling technique, yearly high-resolution OMI maps for the whole domain of India are created, and they reveal a continuous increase in SO2 columns over India. Power plant regions with annual SO2 emissions greater than 50 Gg year-1 produce statistically significant OMI signals, and a high correlation (R equals 0.93) is found between SO2 emissions and OMI-observed SO2 burdens. Contrary to the decreasing trend of national mean SO2 concentrations reported by the Indian Government, both the total OMI-observed SO2 and average SO2 concentrations in coal-fired power plant regions increased by greater than 60 percent during 2005-2012, implying the air quality monitoring network needs to be optimized to reflect the true SO2 situation in India.

SO2↗

Intelligent sensor-model automated control of PMR-15 autoclave processing

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Hart, S.↗

Improvements and Additions to NASA Near Real-Time Earth Imagery

For many years, the NASA Global Imagery Browse Services (GIBS) has worked closely with the Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) system to provide near real-time imagery visualizations of AIRS (Atmospheric Infrared Sounder), MLS (Microwave Limb Sounder), MODIS (Moderate Resolution Imaging Spectrometer), OMI (Ozone Monitoring Instrument), and recently VIIRS (Visible Infrared Imaging Radiometer Suite) science parameters. These visualizations are readily available through standard web services and the NASA Worldview client. Access to near real-time imagery provides a critical capability to GIBS and Worldview users. GIBS continues to focus on improving its commitment to providing near real-time imagery for end-user applications. The focus of this presentation will be the following completed or planned GIBS system and imagery enhancements relating to near real-time imagery visualization.

near real time↗