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NASA NTRS2020

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗
NASA NTRS2021

Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land–atmosphere model (GFDL AM4.0/LM4.0)

Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Many dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and land surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of the wind erosion threshold (V(threshold)) over dry and sparsely vegetated surfaces. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land–atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and the seasonal cycle of DOD are better captured over the “dust belt” (i.e., northern Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean V(threshold), all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycles as well as dust forecasting.

Bing Pu↗
NASA NTRS2020

Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark‐Target Algorithm: 1. Dust Detection

To prepare for implementation of a new aerosol retrieval specifically designed for dust aerosol over ocean in the operational Dark-Target (DT) algorithms for the Moderate-resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors, we focus on the challenge of detecting dust. We first survey the literature on existing dust detection algorithms and then develop an innovative algorithm that combines near-UV (deep blue), visible, and thermal infrared (TIR) wavelength spectral tests. The new detection algorithm is applied to Terra and Aqua MODIS granules and compared with other dust detection possibilities from existing MODIS products. Quantitative evaluation of the new dust detection algorithm is conducted using both a collocated AERONET-MODIS data set and collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-MODIS data set. From comparison with both AERONET and CALIOP measurements, we estimate the new dust detection algorithm detects about 30% of weakly dusty pixels and more than 80% of heavily dusty pixels, with false detections in the range of 1–2%. The very low false detection rate is particularly noteworthy in comparison with existing literature. Compared with the dust flag currently available as part of the MODIS cloud mask product (MOD35/MYD35), and dust classification based on commonly used thresholds with aerosol optical depth (AOD) and Angstrom exponent (AE), the new dust detection algorithm finds more dusty pixels and fewer false detections.

spectral dust detection↗
NASA NTRS2019

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗
NASA NTRS2021

Evaluation of Novel NASA MODIS and VIIRS Aerosol Products and Assessment of Smoke Height Boundary Layer Ratio During Extreme Smoke Events in the Western U.S.

We analyze new aerosol products from NASA satellite retrievals over the western U.S. during August 2013, with special attention to locally generated wildfire smoke and downwind plume structures. Aerosol optical depth (AOD) at 550 nm from MODIS (Terra and Aqua Collections 6 and 6.1) and VIIRS Deep Blue (DB) and MODIS (Terra and Aqua) Multi‐Angle Implementation of Atmospheric Correction (MAIAC) retrievals are evaluated against ground‐based AErosol RObotic NETwork (AERONET) observations. We find a significant improvement in correlation with AERONET and other metrics in the latest DB AOD (MODIS C6.1 r^2=0.75, VIIRS r^2=0.79) compared to MODIS C6 (r2=0.62). In general, MAIAC (r^2=0.84) and DB (MODIS C6.1 and VIIRS) present similar statistical evaluation metrics for the western U.S. and are useful tools to characterize aerosol loading associated with wildfire smoke. We also evaluate three novel NASA MODIS plume injection height (PIH) products, one from MAIAC and two from the Aerosol Single scattering albedo and layer Height Estimation (ASHE) (MODIS and VIIRS) algorithm. Both Terra and Aqua MAIAC PIHs statistically agree with ground‐based and satellite lidar observations near the fire source, as do ASHE, although the latter is sensitive to assumptions about aerosol absorption properties. We introduce a first‐order approximation Smoke Height Boundary Layer Ratio (SHBLR) to qualitatively distinguish between aerosol pollution within the planetary boundary layer and the free troposphere. We summarize the scope, limitations, and suggestions for scientific applications of surface level aerosol concentrations specific to wildfire emissions and smoke plumes using these novel NASA MODIS and VIIRS aerosol products.

Plume injection height↗
NASA NTRS2021

Air Pollution Scenario over Pakistan: Characterization and Ranking of Extremely Polluted Cities using Long-Term Concentrations of Aerosols and Trace Gases

Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectroradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used. For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 μg/cu. m, over all Pakistan from 2003 to 2020. This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 μg/cu. m annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 <35 μg/cu. m). The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan’s air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries. Statistically significant positive (increasing) trends in PM1, PM2.5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in ~89%, ~67%, ~48%, 91%, and ~88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.

Muhammad Bilal↗
NASA NTRS2023

Assessment of the Impact of Discontinuity in Satellite Instruments and Retrievals on Global PM2.5

Exposure to fine particulate matter (PM2.5) is the leading environmental risk factor for mortality globally. Satellite-derived estimates of surface PM2.5 developed from a combination of satellites, simulations, and ground monitor data are relied upon for health impact studies. The ability to develop satellite-derived PM2.5 estimates requires the continued availability of aerosol optical depth (AOD) sources. This work examines the impact of the addition or loss of satellite AOD data sources on global PM2.5 estimation and the impact of continuing the longterm record with AOD from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar orbiting Partnership (S-NPP) satellite after the loss of the MODIS (MODerate resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer) instruments on board the Terra and Aqua satellites. We find that the addition of VIIRS S-NPP AOD products to geophysical PM2.5 estimates from satellites and simulations causes regional differences that correspond to differences in the VIIRS and MODIS Deep Blue AOD algorithms and sampling. Changes in long-term trends and timeseries due to the addition or loss of AOD data sources are generally within their uncertainties. Statistical fusion with ground monitor data partially corrects for changes due to sampling differences when introducing the VIIRS AOD products, but uncertainty remains over desert regions where ground monitor coverage is sparse. This work provides promise for the sustained development of global satellite-derived PM2.5 estimates, despite discontinuities in instruments and retrieval methods.

Remote sensing↗
NASA NTRS2022

Characterizing Aerosol From Space With the MODerate Resolution Imaging Spectroradiometer (Modis) on the Terra and Aqua Satellites

Aerosols, the small, suspended liquid and solid particles in the atmosphere, have myriad effects on climate, weather, and air quality. When the NASA Earth-Observing System’s (EOS) Terra and Aqua satellites launched in 1999 and 2002, they each included many advanced sensors that have been used for aerosol research. In particular, the MODerate-resolution Imaging Spectroradiometer (MODIS) deployed on both satellites, has provided key data relating to aerosol loading and relative aerosol type on the global scale. Three different algorithms, known as “Dark Target”, “Deep Blue” and “MAIAC”, use different subsets of MODIS measurements and different assumptions to create various products such as Aerosol Optical Depth (AOD), fine mode fraction (FMF) and single scattering albedo (SSA). Although all three derive AOD in cloud-free conditions, each algorithm has different strengths and weaknesses in different areas of the globe and under different conditions. Here, we provide a short summary of each algorithm, description of products, and basic information about downloading and using the products. We also provide some examples of how MODIS aerosol products are used. Finally, we add a quick discussion about how these algorithms and products will continue after MODIS leaves orbit.

MODIS↗
NASA NTRS1990

Ionized interstellar froth in irregular galaxies

The warm interstellar medium of galaxies is a complicated place. It is often full of holes, neutral and ionized loops and shells, and diffuse ionized gas. Deep H alpha images of Magellanic-type irregular galaxies also reveal complex spatial structures consisting of loops and filaments in the interstellar gas outside of the boundaries of traditional HII regions. Researchers refer to these ionized structures as froth. Such structures could mark paths over which newly produced heavy elements are dispersed in irregular galaxies, and they could be the signatures of a feedback process related to star formation. In order to investigate the physical nature of the froth, researchers obtained narrow-band images and high and low dispersion spectra from Kitt Peak National Observatory (KPNO) and deep blue-passband plates from the Canada-France-Hawaii Observatory (CFHO).

Hunter, Deidre A.↗
NASA NTRS1991

Galaxies clustering around QSOs with z = 0.9-1.5 and the origin of blue field galaxies

Deep CCD images were obtained in Mould-Cousins R and I passbands of 16 radio quasars with z values between 0.9 and 1.5 and absolute values of b above 35 deg, chosen from the Veron-Cetty and Veron (1984) catalog. Results indicate that, in this population of radio quasars, there is a statistically significant excess of galaxies within 15 arcsec of the quasars and brighter than R = 23 and I = 22. However, contrary to the report of Tyson (1986), no excess was found of galaxies with R less than 21 lying within 30 arcsec of quasars in this redshift range. Data were also obtained for very blue galaxies seen among objects in the general field, all of which are bluer in R-I than Magellanic irregulars at any redshift less than 3. It is suggested that this population might be comprised of low-redshift low-luminosity (H II region) galaxies of the type studied by French (1980) and/or higher redshift galaxies with strong cooling flows and forbidden O II lines.

Hintzen, Paul↗
NASA NTRS1993

Deep galaxy count predictions in the radio, infrared, and X-ray spectral bands

The existence of a dominant population of strongly evolving starburst sources at moderate redshift is a plausible explanation for the excess number of faint blue galaxies detected in deep sky surveys. Multiwavelength observations at faint magnitudes would allow the existence of such a population to be confirmed. We use observed luminosity correlations and physical properties of known starburst galaxies to predict their contribution to the deep radio, infrared, and X-ray counts, as well as to the diffuse extragalactic background radiation in these various spectral bands.

Treyer, Marie-Agnes↗
NASA NTRS1992

The unusual field of the quasar 3C 336 - Identification of three foreground Mg II absorbing galaxies

Imaging and spectroscopic observations of the field of the QSO 3C 336 (z = 0.927), whose absorption spectrum exhibits at least three Mg II 2796, 2803-A absorption systems with z sub abs less than z sub em, making it the richest low-redshift absorption spectrum observed in a recently completed absorption line survey. The most intrinsically faint Mg II absorbing galaxy yet discovered is tentatively identified. With z equal to 0.472 and B greater than 24, its properties strongly resemble those of the so-called faint blue galaxies found in deep imaging and spectroscopic surveys for field galaxies. The implications of this very complex field for the general properties of galaxies producing heavy element absorption systems in the spectra of QSOs are discussed.

Steidel, Charles C.↗
NASA NTRS1993

Simulations of Deep Galaxy Fields I: Monte-Carlo Simulations of Optical and Near Infrared Counts

Monte-Carlo simulations of three dimensional galaxy distributions are performed, following the prescription of Chokishi & Wright (1988), to study the photometric properties of evolving galaxy populations in the optical and near infrared bands to high redshifts. Galaxies are spatially distributed according to the spatial two point correlation function in a range of cluster to field environments andin volume elements appropriate to the cosmological model under consideration. Details of individual galaxy properties, including luminosities, morphologies, disk-to-bulge ratios, and size distributions are simulated to match local observed galaxy properties. Galaxies have evolving gas fraction, metallicity and spectral energy distributions that include both stellar emission and internal dust absorption and re-emission. The simulations result in noiseless two dimensional galaxy distributions on the sky that canbe compared to the observed deep images in the blue and near-infrared bands...

faint↗
DOE OSTI2025

Automated Programmable Logic Controller Memory Forensics Using RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and Internet-based technologies has enhanced industrial control system operations but have inadvertently increased their vulnerabilities to cyber attacks. When an industrial control system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies. Memory forensics is critical in the incident analysis process to ascertain what occurred. Approaches for analyzing the persistent memory in industrial control devices are limited and almost nonexistent for volatile memory. This chapter proposes an automated methodology for programmable logic controller memory dump analysis using computer vision and deep learning techniques. The methodology converts the sequences of bytes in a programmable logic controller memory dump to red-green-blue pixels and employs a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. The trained model is employed to automatically segment new memory images and identify forensic artifacts. Evaluation of the methodology on a Schneider Electric Modicon M221 programmable logic controller under code injection and code modification attacks demonstrates its ability to detect attack artifacts in memory dumps.

Asmar Awad, Rima [ORNL] (ORCID:0000000233407742)↗
NASA NTRS2014

Investigating the Present Day Cosmic Dust Flux at the Earth's Surface: Initial Results from the Kwajalein Micrometeorite Collection

Examination of impact craters on the Long Duration Exposure Facility satellite indicate a present day micrometeoroid flux of approx. 30,000 tonnes [1 after 2]. But what portion of this material arrives at the Earth's surface as micrometeorites? Studies of available micrometeorite collections from deep sea sediments [e.g. 3], Greenland blue ice [e.g. 4] and the South Pole water well [e.g. 1] may be complicated by terrestrial weathering and, in some cases, collection bias (magnetic separation for deep sea sediments) and poorly constrained ages. We have recently set up a micrometeorite collection station on Kwajalein Island in the Republic of the Marshall Islands in the Pacific Ocean, using high volume air samplers to collect particles directly from the atmosphere. By collecting in this way, the terrestrial age of the particles is known, the weathering they experience is minimal, and we are able to constrain particle arrival times. Collecting at this location also exploits the considerably reduced anthropogenic background [5]. Method: High volume air samplers were installed on top of the two-story airport building on Kwajalein. These were fitted with polycarbonate membrane filters with 5μm diameter perforations. The flow rates were set to 0.5m3/min, and filters were changed once a week. After collection, filters were washed to remove salt and concentrate particles [see 5] in preparation for analysis by SEM. Results and Discussion: A selection of filters have been prepared and surveyed. Due to their ease of identification our initial investigations have focused on particles resembling cosmic spherules. The spheres can be divided into three main groups: 1. Silicate spherules rich in Al, Ca, K and Na (to varying degrees), 2. Silicate spherules rich in Mg and Fe and 3. Fe-rich spherules. Group 1 spherules are often vesiculated and can occur as aggregates. They are similar in appearance and composition to volcanic microspheres [e.g. 6] and are thus likely terrestrial in origin (volcanic). Those of groups 2 and 3, however, typically exhibit quenched surface textures consistent with cosmic spherules. Initial results suggest there is significant variation in the abundance of these groups from filter to filter. Work is ongoing to fully characterize these spherules and to constrain their flux with time.

Wozniakiewicz, P. J.↗
NASA NTRS1995

Succinate dehydrogenase activity and soma size of motoneurons innervating different portions of the rat tibialis anterior

The spatial distribution, soma size and oxidative enzyme activity of gamma and alpha motoneurons innervating muscle fibres in the deep (away from the surface of the muscle) and superficial (close to the surface of the muscle) portions of the tibialis anterior in normal rats were determined. The deep portion had a higher percentage of high oxidative fibres than the superficial portion of the muscle. Motoneurons were labelled by retrograde neuronal transport of fluorescent tracers: Fast Blue and Nuclear Yellow were injected into the deep portion and Nuclear Yellow into the superficial portion of the muscle. Therefore, motoneurons innervating the deep portion were identified by both a blue fluorescent cytoplasm and a golden-yellow fluorescent nucleus, while motoneurons innervating the superficial portion were identified by only a golden-yellow fluorescent nucleus. After staining for succinate dehydrogenase activity on the same section used for the identification of the motoneurons, soma size and succinate dehydrogenase activity of the motoneurons were measured. The gamma and alpha motoneurons innervating both the deep and superficial portions were located primarily at L4 and were intermingled within the same region of the dorsolateral portion of the ventral horn in the spinal cord. Mean soma size was similar for either gamma or alpha motoneurons in the two portions of the muscle. The alpha motoneurons innervating the superficial portion had a lower mean succinate dehydrogenase activity than those innervating the deep portion of the muscle. An inverse relationship between soma size and succinate dehydrogenase activity of alpha, but not gamma, motoneurons innervating both the deep and superficial portions was observed. Based on three-dimensional reconstructions within the spinal cord, there were no apparent differences in the spatial distribution of the motoneurons, either gamma or alpha, associated with the deep and superficial compartments of the muscle. The data provide evidence for an interdependence in the oxidative capacity between a motoneuron and its target muscle fibres in two subpopulations of motoneurons from the same motor pool, i.e. the same muscle.

NASA Discipline Musculoskeletal↗