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6 results for “Aircraft emissions”
CEDS Version 2021-04-21 Aircraft Emissions Fix
<p>This data release contains global CEDS aircraft emissions gridded over a 0.5° latitude x longitude grid, with 25 altitude levels of 0.61 km thickness. The center of these altitude levels range from 0.305 to 14.495 km above sea level. Grids are provided over the years 1950-2019 on a monthly time scale, with the exception of methane, which ranges from 1970-2019. </p>
Supporting information for the paper: Constraints on recoil leader properties estimated from X-ray emission in aircraft triggered discharges
<p>Supporting information for the paper: Constraints on recoil leader properties estimated from X-ray emission in aircraft triggered discharges consisting of 18 data files, sorted by figure the data appears in. See 0_READ_ME for information about the individual files and variables.</p>
Data from: Take-off engine particle emission indices for in-service aircraft at Los Angeles International Airport
We present ground-based, advected aircraft engine emissions from flights taking off at Los Angeles International Airport. 275 discrete engine take-off plumes were observed on 18 and 25 May 2014 at a distance of 400 m downwind of the runway. CO2 measurements are used to convert the aerosol data into plume-average emissions indices that are suitable for modelling aircraft emissions. Total and non-volatile particle number EIs are of order 1016–1017 kg−1 and 1014–1016 kg−1, respectively. Black-carbon-equivalent particle mass EIs vary between 175–941 mg kg−1 (except for the GE GEnx engines at 46 mg kg−1). Aircraft tail numbers recorded for each take-off event are used to incorporate aircraft- and engine-specific parameters into the data set. Data acquisition and processing follow standard methods for quality assurance. A unique aspect of the data set is the mapping of aerosol concentration time series to integrated plume EIs, aircraft and engine specifications, and manufacturer-reported engine emissions certifications. The integrated data enable future studies seeking to understand and model aircraft emissions and their impact on air quality.
Four-dimensional aircraft emission inventory dataset of Landing and take-off cycle in China from 2019 to 2023
<p>Aircraft emissions during landing and takeoff (LTO) having unique three-dimensional spatial characteristics and typical hourly temporal variations. In order to further investigate the adverse effects of aircraft emissions, the adverse effects for aircraft emissions, this study integrated the emission calculation and flight trajectory recognition methods to establish a four-dimensional aircraft emission inventory dataset of China’s LTO cycle (4D-LTO emission inventory dataset) from 2019 to 2023. The dataset has a high spatial-temporal resolution (hourly, 0.03° × 0.03° × 34 height layers).</p> <p>Information for 4D-LTO emission inventory dataset during 2019-2023:</p> <p>Species: NOx.</p> <p>Number of airports included in different years: 2019 (237 airports), 2020 (239 airports), 2021 (248 airports), 2022 (254 airports), 2023 (257 airports).</p> <p>Temporal information: 2019 (8760 hours), 2020 (8784 hours), 2021 (8760 hours), 2022 (8760 hours), 2023 (8760 hours).</p> <p>Spatial information: The horizontal resolution of the 4D-LTO emission inventory is 0.03° × 0.03° with the latitude and longitude range of 3.40°N–53.56°N and 73.44°E–135.09°E, respectively. The altitude resolution was divided into 34 layers from 0 m to 15668 m (0.0 m–38.3 m, 38.3 m–76.7 m, 76.7 m–115.3 m, 115.3 m–154 m, 154 m–231.8 m, 231.8 m–310.3 m, 310.3 m–389.3 m, 389.3 m–469 m, 469 m–549.3 m, 549.3 m–630.3 m, 630.3 m–711.9 m, 711.9 m–794.2 m, 794.2 m–960.7 m, 960.7 m–1130.1 m, 1130.1 m–1302.3 m, 1302.3 m–1477.6 m, 1477.6 m–1656.0 m, 1656.0 m–1929.7 m, 1929.7 m–2211.1 m, 2211.1 m–2599.3 m, 2599.3 m–3107.2 m, 3107.2 m–3643.1 m, 3643.1 m–4210.5 m, 4210.5 m–4813.9 m, 4813.9 m–5458.5 m, 5458.5 m–6151.2 m, 6151.2 m–6900.4 m, 6900.4 m–7717.4 m, 7717.4 m–8617.3 m, 8617.3 m–9621.2 m, 9621.2 m–10759.7 m, 10759.7 m–12080.6 m, 12080.6 m–13664.8 m, 13664.8 m–15668 m.).</p>
Data from: Take-off engine particle emission indices for in-service aircraft at Los Angeles International Airport
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CARVE: Ecosystem Scale CH4 Emission Derived from Aircraft Observations 2012-2014
This dataset provides methane flux estimates derived from airborne measurements collected over Alaska and the western Yukon Territory during the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) between 2012 and 2014. The state-scale methane fluxes were calculated using a combination of atmospheric profiles and lagrangian transport modeling. The methane flux estimates were used in a simple linear regression model to estimate the fluxes from the tundra and boreal ecosystems. Methane fluxes were also used with a combination of environmental variables to derive a statistical relationship between domain-wide flux and soil temperature. Soil temperature products from North American Regional Reanalysis and derived parameters from a Boltmann-Arrhenius model were used to model methane flux and related uncertainties within the domain at monthly and daily frequencies.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.