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At least 145 records · Page 8

Infrared spectra of crystalline phase ices condensed on silicate smokes at T less than 20 K

Infrared spectra of H2O, CH3OH, and NH3 condensed at T less than 20 K on amorphous silicate smokes reveal that predominantly crystalline phase ice forms directly on deposit. Spectra of these molecules condensed on aluminum substrates at T less than 20 K indicate that amorphous phase ice forms. On aluminum, crystalline phase H2O and CH3OH are formed by annealing amorphous deposits to 155 K and 130 K, respectively (or by direct deposit at these temperatures); crystalline NH3 is formed by direct deposit at 88 K. Silicate smokes are deposited onto aluminum substrates by evaporation of SiO solid or by combustion of SiH4 with O2 in flowing H2 followed by vapor phase nucleation and growth. Silicate smokes which are oxygen-deficient may contain active surface sites which facilitate the amorphous-to-crystalline phase transition during condensation. Detailed experiments to understand the mechanism are currently in progress. The assumption that amorphous phase ice forms routinely on grains at T less than 80 K is often used in models describing the volatile content of comets or in interpretations of interstellar cloud temperatures. This assumption needs to be reexamined in view of these results.

Moore, Marla H.↗

Smoke detection in low-G fires

Fires in spacecraft are considered a credible risk. To respond to this risk, NASA flew fire detectors on Skylab and the Space Shuttle (STS) and included them in the design for International Space Station Alpha (ISSA). In previous missions (Mercury, Gemini and Apollo), the crew quarters were so cramped that it was not considered credible that the astronauts could fail to observe a fire. The Skylab nodule included approximately 20 UV fire detectors. The space shuttle has 9 ionization detectors in the mid deck and flight deck and Spacelab has six additional ionization detectors. The planned detectors for ISSA are laser-diode, forward-scattering, smoke or particulate detectors. Current plans for the ISSA call for two detectors in the open area of the module and detectors in racks that have both cooling air flow and electrical power. Due to the complete absence of data concerning the nature of particulate and radiant emission from low-g fires, all three of these detector systems were designed based upon 1-g test data. As planned mission durations and complexity increase and the volume of spacecraft increases, the need for and importance of effective, crew independent, fire detection grows significantly. This requires more knowledge concerning low-gravity fires and how they might be detected. To date, no combustion-generated particulate samples have been collected for well-developed microgravity flames. All of the extant data come from drop tower tests and therefore only correspond to the early stages of a fire. The fuel sources were restricted to laminar gas-jet diffusion flames and rapidly overheated wire insulation. These gas-jet drop tower tests indicate, through thermophoretic sampling, that soot primaries and aggregates (groups of primary particles) in micro-g may be significantly larger than those in normal-g (ng). This raises new scientific questions about soot processes as well as practical issues for particulate detection/alarm threshold levels used in on-orbit smoke detectors. Furthermore, it is widely speculated but unverified that the aggregates will grow to very large scales in a microgravity fire of longer duration than available on the ground. Preliminary tests in the 2.2 second drop tower suggest that particulate generated by overheated wire insulation will also be larger in microgravity than in normal gravity. TEM grids downstream of the fire region in the WIF experiment as well as visual observation of long string-like aggregates, further confirm this suggestion. The combined impact of these limited results and theoretical predictions is that direct knowledge of low-g combustion particulate as opposed to extrapolation from 1-g data is needed for a more confident design of smoke detectors for spacecraft.

Urban, David L.↗

The Efficiency of the Smoke Meter at Characterizing Engine Emissions

The effectiveness of a smoke meter's ability to characterize the particulate emissions of a jet fuel combustor was evaluated using the University of Missouri-Rolla Mobile Aerosol Sampling System (UMR-MASS). A burner simulating an advanced jet engine combustor design was used to generate typical combustion particulates, which were then analyzed by the smoke meter. The same particulates were then size discriminated to ascertain the effective impact of aerosol diameter on smoke number readings.

Paladino, Jonathan D.↗

Cloud Classification in Polar and Desert Regions and Smoke Classification from Biomass Burning Using a Hierarchical Neural Network

This research focuses on a new neural network scene classification technique. The task is to identify scene elements in Advanced Very High Resolution Radiometry (AVHRR) data from three scene types: polar, desert and smoke from biomass burning in South America (smoke). The ultimate goal of this research is to design and implement a computer system which will identify the clouds present on a whole-Earth satellite view as a means of tracking global climate changes. Previous research has reported results for rule-based systems (Tovinkere et at 1992, 1993) for standard back propagation (Watters et at. 1993) and for a hierarchical approach (Corwin et al 1994) for polar data. This research uses a hierarchical neural network with don't care conditions and applies this technique to complex scenes. A hierarchical neural network consists of a switching network and a collection of leaf networks. The idea of the hierarchical neural network is that it is a simpler task to classify a certain pattern from a subset of patterns than it is to classify a pattern from the entire set. Therefore, the first task is to cluster the classes into groups. The switching, or decision network, performs an initial classification by selecting a leaf network. The leaf networks contain a reduced set of similar classes, and it is in the various leaf networks that the actual classification takes place. The grouping of classes in the various leaf networks is determined by applying an iterative clustering algorithm. Several clustering algorithms were investigated, but due to the size of the data sets, the exhaustive search algorithms were eliminated. A heuristic approach using a confusion matrix from a lightly trained neural network provided the basis for the clustering algorithm. Once the clusters have been identified, the hierarchical network can be trained. The approach of using don't care nodes results from the difficulty in generating extremely complex surfaces in order to separate one class from all of the others. This approach finds pairwise separating surfaces and forms the more complex separating surface from combinations of simpler surfaces. This technique both reduces training time and improves accuracy over the previously reported results. Accuracies of 97.47%, 95.70%, and 99.05% were achieved for the polar, desert and smoke data sets.

Alexander, June↗

Satellite Remote Sensing of Fires, Smoke and Regional Radiative Energy Budgets

Using satellite imagery, more than five million square kilometers of the forest and cerrado regions over South America are extensively studied to monitor fires and smoke during the 1985 and 1986 biomass burning season. The results are characterized for four major eco-systems, namely: (1) Tropical Rain Forest (TRF), (2) Tropical Broadleaf Seasonal (TBS), (3) Mild/Warm/Hot Grass/Shrub (MGS), and (4) Savanna/Grass and Seasonal Woods (SGW). Using collocated measurements from the instantaneous scanner Earth Radiation Budget Experiment [ERBE) data, the direct regional radiative forcing of biomass burning aerosols are computed. The results show that more than 70% of the fires occur in the MGS and SGW eco-systems due to agricultural practices. The smoke generated from biomass burning has negative net radiative forcing values for all four major ecosystems within South America. The smoke found directly over the fires have mean net radiative forcing values ranging between -25.6 to -33.9 W/sq m for 1985 and between -12.9 to -40.8 W/sq m for 1986. These results confirm that the regional net radiative impact of biomass burning is one of cooling.

Christopher, Sundar A.↗

Airborne lidar observations of smoke haze during SCAR-B 1995

The Smoke, Clouds, Aerosol, and Radiation Brazil(SCAR-B) field campaign was conducted to study the effects that widespread and persistent biomass burning have upon radiative and chemical processes in the atmosphere. The radiative transfer characteristics of the atmosphere are altered by the introduction of particulate and gaseous materials which are the products of the combustion of vegetative material at ground level. These substances are transported and distributed horizontally and vertically by atmospheric dynamical processes which may be perturbed by the heat energy from the fires. As the pollutants disperse, their physical and chemical properties change substantially. A complete description of the effects of smoke requires that the evolution back to the natural situation be fully examined. A most important component of smoke haze investigation is finding its vertical and horizontal distribution in relation to the driving factors of dynamics and the related horizontal transport. In this presentation, we employ data from the Cloud Lidar System(CLS), carried aboard the NASA ER-2 aircraft, to provide a unique view of the particulate or aerosol loading produced by fires, especially with regard to the geometrical distribution of the aerosols in the vertical plane. The lidar has the ability to measure aerosol optical properties in a continuous fashion at quite fine vertical and horizontal resolution. The results from the lidar provide measurements that are largely independent of influences that corrupt passive instruments and thus it can serve to corroborate their results. The extended horizontal and vertical range of lidar results can also augment ground based and airborne in situ measurements which have limited horizontal and vertical scope. We present the results of our analysis of CLS observations taken during the SCAR-B field campaign. Observations of the the aerosol optical thickness from the Aerosol Robotic Network(AERONET) of solar photometers are employed in conjunction with CLS data to derive extinction to backscatter ratio values which are used to convert the lidar backscatter coefficient into extinction coefficient. The extinction coefficient is integrated vertically to find aerosol optical thickness along ER-2 flight tracks. We use images of the CLS derived extinction coefficient to depict its horizontal and vertical distribution. Multispectral photometer optical thickness is used to compute the Angstrom exponent. With these, we examine the hypothesis that the values of extinction to backscatter ratio can be related to the Anstrom coefficient since both of these would be a function of the refractive index and size distribution of the aerosols.

Hart, William D.↗

Biomass-Burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA)

Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth- atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth s radiation and water budget. Analyses from satellite measurements reveal the reflected solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by 100 (20) Watts per square meter over the month of March 2000. In addition, the reduction in cloud spectral reflectance is large enough to lead to significant errors in satellite retrievals of cloud properties (e.g., optical thickness and effective radius). The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, ground-based networks and dedicated field experiments. BASE-ASIA initiative has been proposed and will be discussed.

Tsay, S.-C.↗

Investigations of Desert Dust and Smoke in the North Atlantic in Support of the TOMS Instrument

During the initial period of the work we concentrated on Saharan dust storms and published a sequence of papers (Colarco et a1 2002,2003a,b, Toon, 2004). The U.S. Air Force liked the dust model so well that they appropriated it for operational dust storm forecasting (Barnum et al., 2004). The Air Force has used it for about 5 yrs in the Middle East where dust storms cause significant operational problems. The student working on this project, Peter Colarco, has graduated and is now a civil servant at Goddard where he continues to interact with the TOMS team. This work helped constrain the optical properties of dust at TOMS wavelengths, which is useful for climate simulations and for TOMS retrievals of dust properties such as optical depth. We also used TOMS data to constrain the sources of dust in Africa and the Middle East, to determine the actual paths taken by Saharan dust storms, to learn more about the mechanics of variations in the optical depths, and to learn more about the mechanisms controlling the altitudes of the dust. During the last two years we have been working on smoke from fires. Black carbon aerosols are one of the leading factors in radiative forcing. The US Climate Change Science Program calls this area out for specific study. It has been suggested by Jim Hansen, and Mark Jacobsen among others, that by controlling emissions of black carbon we might reduce greenhouse radiative forcing in a relatively painless manner. However, we need a greatly improved understanding of the amount of black carbon in the atmosphere, where it is located, where it comes from, how it is mixed with other particles, what its actual optical properties are, and how it evolves. In order to learn about these issues we are using a numerical model of smoke. We have applied this model to the SAFARI field program data, and used the TOMS satellite observations in that period (Sept. 2000). Our goal is to constrain source function estimates for black carbon, and smoke optical properties.

Toon, Owen B.↗

Measurement of Fire Radiative Energy from Space and Implications for Fire-Disaster Monitoring and Smoke Emissions Modeling

Measurement of fire radiative energy (FRE) release rate or power (FRP) from satellite provides a vital mechanism for distinguishing different strengths of fires. Analysis of 1-km resolution fire data, acquired globally by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites from 2000 to 2006, showed instantaneous FRP values ranging between 0.02 MW and 1866 MW, to which simple thresholds can be applied to categorize fires by strength, in a similar fashion as the strengths of earthquakes and hurricanes. Analysis of regional mean FRP per unit area of land (FRP flux) shows that at peak fire season in certain regions, fires can be responsible for up to 0.2 W/m2 at peak time of day. When considered as the active fire contribution to the direct surface radiative forcing (RF) in the different fire regions, this order of magnitude of FRF fluxes is non negligible. It has been determined experimentally that the amount of FRE released by a fire over the course of its duration is directly proportional to the amount of biomass consumed by it. Furthermore, at the satellite observation scale, the rate of release of FRE (i.e. FRP) is proportional to the rate of biomass consumption, and that of emission of smoke particulates and eventually also other smoke constituents. Therefore, current research efforts are geared toward deriving simple parameterizations that will facilitate direct input of FRP measurements in models, not only to improve the accuracy of burned-biomass and smoke emissions estimations, but also to reduce the hitherto practiced heavy reliance on multiple indirect parameters with indeterminate uncertainties.

Ichoku, Charles↗

Radiative Effects of African Dust and Smoke Observed from CERES and CALIOP Data

Cloud and aerosol effects have a significant impact on the atmospheric radiation budget in the Tropical Atlantic because of the spatial and temporal extent of desert dust and smoke from biomass burning in the atmosphere. The influences of African dust and smoke aerosols on cloud radiative properties over the Tropical Atlantic Ocean were analyzed for the month of July for three years (2006-2008) using collocated data collected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Clouds and the Earth s Radiant Energy System (CERES) instruments on the CALIPSO and Aqua satellites. Aerosol layer height and type can be more accurately determined using CALIOP data, through parameters such as cloud and aerosol layer height, optical depth and depolarization ratio, than data from atmospheric imagers used in previous cloud-aerosol interaction studies. On average, clouds below 5 km had a daytime instantaneous shortwave (SW) radiative flux of 270.2 +/- 16.9 W/sq m and thin cirrus clouds had a SW radiative flux of 208.0 +/- 12.7 W/sq m. When dust aerosols interacted with clouds below 5 km, as determined from CALIPSO, the SW radiative flux decreased to 205.4 +/- 13.0 W/sq m. Similarly, smoke aerosols decreased the SW radiative flux of low clouds to a value of 240.0 +/- 16.6 W/sq m. These decreases in SW radiative flux were likely attributed to the aerosol layer height and changes in cloud microphysics. CALIOP lidar observations, which more accurately identify aerosol layer height than passive instruments, appear essential for better understanding of cloud-aerosol interactions, a major uncertainty in predicting the climate system.

Yorks, John E.↗

Smoke Detection for the Orion Crew Exploration Vehicle

The Orion Crew Exploration Vehicle (CEV) requires a smoke detector for the detection of particulate smoke products as part of the Fire Detection and Suppression (FDS) system. The smoke detector described in this paper is an adaptation of a mature commercial aircraft design for manned spaceflight. Changes made to the original design include upgrading the materials and electronic to space-qualified parts, and modifying the mechanical design to withstand launch and landing loads. The results of laboratory characterization of the response of the new design to test particles are presented.

Sutin, Brian M.↗

Properties of Smoke from Overheated Materials in Low-Gravity

Smoke particle size measurements were obtained under low-gravity conditions by overheating several materials typical of those found in spacecraft. The measurements included integral measurements of the smoke particles and physical sample of the particles for Transmission Electron Microscope analysis. The integral moments were combined to obtain geometric mean particle sizes and geometric standard deviations. These results are presented with the details of the instrument calibrations. The experimental results show that, for the materials tested, a substantial portion of the smoke particles are below 500 nm in diameter.

Urban, David L.↗

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

Lyapustin, A.↗

Aeronet-based Microphysical and Optical Properties of Smoke-dominated Aerosol near Source Regions and Transported over Oceans, and Implications for Satellite Retrievals of Aerosol Optical Depth

Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad families of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA 0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA 0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savanna at Mongu (Zambia), with average SSA 0.85 in the midvisible. These can serve as candidate sets of aerosol microphysicaloptical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.

AERONET↗

Pixel-Based Smoke Detection with Neural Network

Exposure to biomass burning has been linked to respiratory and cardiovascular illnesses in humans. Traditional satellite based visual and multispectral smoke detection methods are not scalable to capabilities of new generations of remote sensing platforms. We develop a scalable, deep learning based detection model capable of identifying smoke pixels using GOES-16 shortwave reflectance data and present a operational web-based tool to visualize smoke predictions.

Ramasubramanian, M.↗

Ozone Production in the Soberanes Smoke Haze: Implications for Air Quality in the San Joaquin Valley During the California Baseline Ozone Transport Study

The Soberanes Fire burned 132,127 acres along the central California coast between July 22 and October 12, 2016, generating dense smoke and a variety of gaseous compounds that drifted eastward into the San Joaquin Valley Air Basin (SJVAB), an ‘extreme’ non‐attainment area for ozone (O3). These gases included nitrogen oxides (NOx) and volatile organic compounds (VOC), the photochemical precursors of O3. The fire started during the California Baseline Ozone Transport Study (CABOTS), a field campaign that brought aircraft, surface, and remote sensing measurements of O3 and related species to central California. In this paper, we use the CABOTS measurements to assess the impact of the Soberanes Fire on ozone and particulate air quality in the SJVAB. We focus our analysis on July 27 ‐ August 2 when the smoke haze was heaviest and the highest O3 concentrations in the SJVAB during 2016 were recorded. Our analyses suggest that while 40 to 60 ppbv of fire‐generated O3 was transported to the eastern SJVAB in the 1‐3 km altitude range, relatively little smoke or fire‐generated O3 reached the surface in the Visalia area.

Andrew O. Langford↗

The Extreme Forest Fires in California/Oregon in 2020: Aerosol Optical and Physical Properties and Comparisons of Aged Versus Fresh Smoke

Wildfire activity in the western United States during August to October 2020 was exceptional in terms of the fire severity and area burned. Extremely dry biomass fuels from near historic multi-year drought conditions were further exacerbated with very hot and dry conditions in 2020. These conditions when coupled with strong offshore flow allowed many ignitions to grow into extremely large and severe wildfires. Long-term monitoring at a few AERONET sites in California showed that the number of days with high Aerosol Optical Depth at 440 nm (AOD 440 >1) in 2020 was greater than any other year going back to the beginning of the data records in 2002. A wide range of fine mode particle volume median radii were retrieved from AERONET data over the course of these fires suggesting significant variability in combustion conditions and aging processes. Additionally, the fine mode radii in some of these smoke plumes in 2020 were very large especially at high AOD (∼0.22–0.32 μm volume median radius), likely due to both coagulation and condensation occurring during aging at very high particulate concentrations. The largest fine mode particle radii combined with narrow distributions resulted in some very rare AOD spectra showing peak AOD at 500 nm and decreasing to lower AOD at both shorter and longer wavelengths. The most extreme retrieved size distributions and associated measured AOD spectra were principally observed in long-distance transported smoke plumes from these western United States fires at sites in Colorado, Maryland and Virginia, possibly due to further aging during transport. Additionally, strong absorption was sometimes observed at short wavelengths with much lower single scattering albedo at 440 nm compared to 675 nm in some plumes consistent with significant brown carbon (BrC) and/or coated black carbon (BC) absorption in biomass burning particles. This strong spectral absorption signature observed at some California sites and dates remained similarly strong in some smoke plumes observed at some east coast sites in Maryland and Virginia, thereby suggesting that the lifetime of these particular BrC and/or coated BC absorbing species was greater than 5 days.

Aerosol↗

Improving Satellite-Based Hotspot Detection Through Deep Learning-Enabled Smoke Recognition

While geostationary satellites, such as the GOES-R series, provide wildland fire hotspot readings at a high temporal resolution, they are prone to false negative readings and decreased confidence. One cause of decreased hotspot confidence is cloud contamination. Smoke produced from wildfire is often misinterpreted as cloud contamination, resulting in inaccurate and unsure sensor readings. To this end, we built a deep learning image segmentation model to identify smoke and cloud in true color satellite images. The model is pre-trained using self-supervised learning on over 10,000 GOES-R images to learn the underlying structure of satellite imagery. Then, the model is fine-tuned on a set of 130 labeled documents using supervised learning. The resulting model performs multi-class image segmentation with 85% accuracy and runs in under a minute on a standard personal computer. When paired alongside hotspot data, the model’s outputs can help increase confidence in wildfire location by identifying cases of cloud contamination that are due to smoke. The resulting model can be deployed in a stand-alone application or bundled in an Open Data Integration for wildland fire management (ODIN) application.

Earth observation↗