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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Wintertime Formaldehyde: Airborne Observations and Source Apportionment Over the Eastern United States

Formaldehyde (HCHO) is generated from direct urban emission sources and secondary production from the photochemical reactions of urban smog. HCHO is linked to tropospheric ozone formation, and contributes to the photochemical reactions of other components of urban smog. In this study pollution plume intercepts during the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign were used to investigate and characterize the formation of HCHO in relation to several anthropogenic tracers. Analysis of aircraft intercepts combined with detailed chemical box modeling downwind of several cities suggest that the most important contribution to observed HCHO was primary emission. A box model analysis of a single plume suggested that secondary sources contribute 21±10% of observed HCHO. Ratios of HCHO/CO observed in the northeast U.S., from Ohio to New York, ranging from 0.2-0.6%, are consistent with direct emissions combined with at most modest photochemical production. Analysis of the nocturnal boundary layer and residual layer from repeated vertical profiling over urban influenced areas indicate a direct HCHO emission flux of 1.3 x 10 14 molecules cm -2 h -1 . In a case study in Atlanta, GA, nighttime HCHO exhibited a ratio to CO (0.6 – 1.8%) and was anti-correlated with O 3 . Observations were consistent with mixing between direct HCHO emissions in urban air masses with those influenced by more rapid HCHO photochemical production. The HCHO/CO emissions ratios determined from the measured data are 2.3 - 15 times greater than the NEI 2017 emissions database. The largest observed HCHO/CO was 1.7 – 1.8%, located near co-generating power stations.

Formaldehyde↗
NASA NTRS2021

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States

Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional scale due to varying parameters among LiDAR data acquisitions and the availability of sufficient calibration data. Here, we present a model using a 3-D convolutional neural network (CNN), a form of deep learning capable of scanning a LiDAR point cloud, combined with coincident satellite data (spectral, phenology, and disturbance history). We compared this approach to traditional modeling used for making forest predictions from LiDAR data (height metrics and random forest) and found that the CNN had consistently lower uncertainty. We then applied the CNN to public data over six New England states in the USA, generating maps of 14 forest attributes at a 10 m resolution over 85% of the region. Aboveground biomass estimates produced a root mean square error of 36 Mg ha−1 (44%) and were within the 97.5% confidence of independent county-level estimates for 33 of 38 or 86.8% of the counties examined. CNN predictions for stem density and percentage of conifer attributes were moderately successful, while predictions for detailed species groupings were less successful. The approach shows promise for improving the prediction of forest attributes from regional LiDAR data and for combining disparate LiDAR datasets into a common framework for large-scale estimation.

Elias Ayrey↗
NASA NTRS2022

Winter Severity Affects Occupancy of Spring- and Summer-Breeding Anurans Across the Eastern United States

Climate change is an increasingly important driver of biodiversity loss. The ectothermic nature of amphibians may make them particularly sensitive to changes in temperature and precipitation regimes, adding to declines from other threats. While active season environmental conditions can influence growth and survival, effects of variation in winter conditions on population dynamics are less well-studied. Given that extreme winter temperatures can influence amphibian survival and fitness, we expected that increased winter severity—as measured by variability in winter temperatures and snow cover—would be associated with decreased occupancy, and that populations that experience more severe winters would have the largest sensitivities and show the greatest declines.

climate↗
NASA NTRSDate not supplied

X-Ray Polarization of the Eastern Lobe of SS 433

IXPE is the first satellite mission dedicated to X-ray polarimetry in the 2–8 keV band. It contains three telescopes, each with a gas-pixel detector sensitive to linear X-ray polarization. IXPE enables imaging X-ray polarimetry of extended sources with an angular resolution of ~30ʺ over a 12ʹ diameter field of view.

x-ray polarimetry, black holes, jets↗