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122 results for “Emission modeling”
Dataset of Modeling of diffuse auroral emission at Mars: Contribution of MeV protons
<p>This dataset contains the input parameters and the simulated results used for figures in the paper "Modeling of diffuse auroral emission at Mars: Contribution of MeV protons" by Y. Nakamura, N. Terada, F. Leblanc, A. Rahmati, H. Nakagawa, S. Sakai, S. Hiruba, R. Kataoka, and K. Murase. Detailed informations about the data files can be found in "README.txt".</p>
A GDM-GTWR Coupled Model for Spatiotemporal Heteroge-neity Quantification of CO2 Emissions: A case of the Yangtze River Delta Urban Agglomeration from 2000 to 2017
<p>The compressed package contains some pictures and data on the paper.</p>
Data from: Modeling 2020 regulatory changes in international shipping emissions helps explain 2023 anomalous warming
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Dataset accompanying: "Applying and Validating Coulomb Rate-and-State Seismicity Models in Acoustic Emission Experiments")
<p>Dataset accompanying: "Applying and Validating Coulomb Rate-and-State Seismicity Models in Acoustic Emission Experiments" by Heimisson, Naderloon, Chandra and Barnhoorn.</p> <p>Please reference the following publication if the data is used:<br><br>Heimisson, E.R., Naderloo, M., Chandra, D. and Barnhoorn, A., 2024. Applying and validating Coulomb rate-and-state seismicity models in acoustic emission experiments. <em>Tectonophysics</em>, p.230574. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.tecto.2024.230574" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.tecto.2024.230574 </span></span></a></p>
Replication Data for: Interpretable machine learning prediction of fire emission and comparison with FireMIP process-based models
<p>The target and predictor variables used in the developed ML model.</p>
Modeling organic aerosol over Europe in summer conditions with the VBS-GECKO parameterization: sensitivity to secondary organic compound properties and IVOC emissions [Dataset]
<p>This dataset is composed of simulation outputs of the CHIMERE model that were used to evaluate the VBS-GECKO SOA parameterization as described in the study :</p> <p>Lannuque, V., Couvidat, F., Camredon, M., Aumont, B., and Bessagnet, B. : Modelling organic aerosol over Europe in summer conditions with the VBS-GECKO parameterization: sensitivity to secondary organic compound properties and IVOC emissions, Atmos. Chem. Phys., <em>to be submitted soon</em>.<br> <br> <strong>Please cite the original ACP article when using these data in a publication.</strong></p> <p><br> The paper also contains more information about how these data were obtained.</p> <p>The dataset is composed of 34 netcdf files. The 17 "daily" files gather the daily averages and the 17 "profile" files present the average day profiles.</p> <p>Victor Lannuque</p>
Modeling the signatures of interaction in Type II supernovae: UV emission, high-velocity features, broad-boxy profiles
<p>Model spectra</p>
Data from: Bayesian modelling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows
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Mechanistic Module for Soil Nitrogen Emissions for CMAQ Model, North America, 2011
This model product provides source code, input data files, and example model outputs for a new mechanistic soil nitrogen (N) module in-line with the Community Multiscale Air Quality (CMAQ) model 5.1 to simulate nitric oxide (NO), nitrous acid (HONO), nitrous oxide (N2O), and ammonia (NH3) soil emissions. The modeling domain covers the continental USA plus portions of northern Mexico and southern Canada, extending from 25 degrees north to 52 degrees north.The simulations use a 12-km spatial grid resolution. Input data are from high-quality reference sources for year 2011. Example model output data are provided for one day, April 21, 2011.
CO2 Observations, Modeled Emissions, and NAM-HYSPLIT Footprints, Boston MA, 2013-2014
This dataset reports continuous atmospheric measurements of CO2 from two receptor sites and three boundary sites in and around Boston, Massachusetts, USA, that were combined with high-resolution CO2 emissions estimates and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to estimate regional CO2 emissions from September 2013 to December 2014. The HYSPLIT model followed an ensemble of 1,000 particles released at the urban CO2 measurement sites backward in time based on wind fields and turbulence from the North American Mesoscale Forecast System (NAM) at 12-km resolution to the boundary CO2 measurement sites to derive footprint values and CO2 enhancements expected from the prior emissions based on the Anthropogenic Carbon Emissions System (ACES) inventory and the urban-Vegetation Photosynthesis Respiration Model (urbanVPRM). This dataset contains three sets of data products: (1) observed hourly mean CO2 observations for two urban receptor sites in Boston, MA (Boston University (BU) and Copley Square (COP)), (2) observed hourly mean CO2 and calculated vertical profiles (50 - 5000 m) for three boundary sites around Boston including Harvard Forest at Petersham, MA (HF), Canaan, NH (CA), and Martha's Vineyard, MA (MVY), and modeled mean boundary CO2 concentrations for particles released from BU and COP, and (3) particle trajectory files including footprint values and CO2 enhancements above boundary CO2 concentrations from the HYSPLIT model.
Global Wetland Methane Emissions derived from FLUXNET and the UpCH4 Model, 2001-2018
This dataset provides monthly globally gridded freshwater wetland methane emissions from 2001-2018 in nmol CH4 m-2 s-1, g C-CH4 m-2 d-1, and TgCH4 grid cell-1 month-1. The data were derived from a six-predictor random forest upscaling model (UpCH4) trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites covering bog (8), fen (8), marsh (10), swamp (6), and wet tundra (11) wetland classes and distributed across Arctic-boreal (20), temperate (16), and (sub)tropical (7) climate zones. Weekly mean CH4 fluxes were computed from half-hourly FLUXNET-CH4 Version 1.0 fluxes. Each grid cell CH4 flux prediction was weighted by fractional grid cell wetland extent to estimate CH4 emissions using the primary global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) product and an alternate Global Inundation Estimate from Multiple Satellites GIEMS version 2 global wetland map. Both WAD2M and GIEMS-2 maps were modified with several correction data layers to represent the monthly area covered by vegetated wetlands, excluding open water and coastal wetlands. The data products are: mean daily fluxes with no adjustment for wetland area (i.e., flux densities assuming hypothetical 100% wetland cover); mean daily fluxes adjusting for WAD2M or GIEMS-2 wetland area; and by-pixel monthly sum of freshwater wetland methane emissions adjusting for WAD2M or GIEMS-2 wetland area. The data are provided in NetCDF4 format.
BDSNP Module for Improved Soil NO Emission Estimates for CMAQ Model, Conterminous USA
This model product provides: (1) the source code for the updated Berkeley-Dalhousie Soil Nitric Oxide (NO) Parameterization module (BDSNP, Version 1.0) as implemented with the Community Multi-scale Air Quality model (CMAQ, Version 5.0.2), (2) module input data from historical and new sources of maps for soil biome type, fertilizer, and arid and non-arid climates, and (3) sample CMAQ simulation outputs for three BDSNP module NO parameterizations (standard, historical, and newer inputs). The simulations use a 12-km spatial grid resolution for CMAQ modeling covering the conterminous United States for July 2011.
Soil N2O emissions from global land ecosystems simulated by the LPJ-GUESS model
<p>This file includes the input and output data for global soil N2O simulations performed with the LPJ-GUESS model. It also contains site-level observations of N2O fluxes from natural vegetation and cropland, sourced from the literature and used for model evaluation. Additional details are available in our recent paper published in <strong>Geoscientific Model Development</strong><em> </em>(<a href="https://doi.org/10.5194/gmd-18-3131-2025">https://doi.org/10.5194/gmd-18-3131-2025</a>).</p>
Impact of negative and positive CO2 emissions on global warming metrics using an ensemble of Earth system model simulations
<p>The data provided here has been used to create the figures in the paper submitted to Biogeosciences titled <em>Impact of negative and positive CO2 emissions on global warming metrics using an ensemble of Earth system model simulations.</em></p>
Characterization Factors for Microplastic Emissions in Life Cycle Assessment Considering Multimedia Fate Modelling
<p>These data provide supporting information for a forthcoming publication proposing new <strong>Regionalized Characterization Factors for Microplastic Emissions in Life Cycle Assessment</strong>. </p> <p>The Characterization Factors (CFs) are developed thanks to a fate model based on SimpleBox4Plastics: https://doi.org/10.5281/zenodo.5743268 and adapted to meet the USEtox methodology. </p> <p>They are derived from the "Regionalized_CFs_for_MP_emissions_in_LCIA.ipynb" script available on GitHub at https://github.com/Julouve/Regionalized_Characterization_Factors_for_Microplastic_Emissions_in_LCIA.git</p> <p>The CFs are developed for 14 polymers (EPS, PP, LDPE, HDPE, PS, PAN, PHA, PA, PLA, strach blend, PBAT, PET, PVC, TRWP) at 5 sizes (1, 10, 100, 1000, 5000 μm) for 9 different regions (North America, Latin America, Europe, Africa & Middle East, Central Asia, Southeast Asia, Northern regions, Oceania, World) for 9 environmental compartments (air, lake water, river water, sea water, their sediment, natural soil, agricultural soil) on two scales (continental & global) and for 3 ecosystems (marine, freshwater and terrestrial). </p> <p>CFs are computed thanks to 2 approaches: a surface approach (in PDF*m2*year/kg) and a species approach (in PDF*year/kg or species*year/kg). </p> <p> </p>
MODELLING GLOBAL ISOPRENE EMISSIONS WITH A SIMPLIFIED PROCESS BASED APPROACH DRIVEN BY THE P-MODEL
<p>Data upload as part of the Master's thesis requirements for the MSc in Computational Methods in Ecology and Evolution at Imperial College, London. </p>
NAEI 2016 UK Emission Data, formatted for the EMEP CTM model.
<p>National Atmospheric Emissions Inventory (NAEI) emissions data for Ammonia (NH3), Carbon Monoxide (CO), Nitrogen Oxides (NOx), Non methane VOCs (VOC), particulate matter <2.5 um (pm25), and particulate matter <10 um (pmco) for the UK. Inventory year is 2016. Original data available from: https://naei.beis.gov.uk/data/mapping</p> <p>This data is in netcdf format, and has been formatted for use with the EMEP air quality model (v4.33 onwards, downloadable from https://github.com/metno/emep-ctm ). The dataset consists of the (1km x 1km) gridded NAEI area sources, for each of the 11 emission sectors (agric, domcom, energyprod, indcom, indproc, nature, offshore, othertrans, roadtrans, solvents, and waste). NAEI point sources have been added to these emissions, allocated to the grid cell in which these sources occur. It is recommended that the user consults the processing scripts for details of this apportionment. The datasets also contain total area source emissions (totarea), and total area plus point source emissions (total), for illustration of the point source contributions.</p> <p>The python scripts used to create this datafiles are available in the 'NAEI_EMEP_Python_Script' directory of this repository: https://zenodo.org/record/3996688#.X0OYQkl7nUJ</p> <p>© Crown 2020 copyright Defra & BEIS via naei.beis.gov.uk, licenced under the Open Government Licence (OGL).</p>
Constraining present-day anthropogenic total iron emissions using model and observations
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Datasets for modelling direct CO2 emissions and uptake at neighborhood scale over the urban area of Beijing
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EMAC/MESSy v2.54.0 model (EMAC) aviation emission inventories as calculated by AirTraf 2.0
<p>The data provided is a ASCII file which contains an aviation emission inventories for one year of a traffic sample over Europe (85 flights) as calculated by AirTraf submodel within the global modelling system EMAC. The submodel AirTraf enabling aircraft trajectory planning is implemented in the chemistry-climate model EMAC with the coupling to the submodel AirTraf. EMAC is a numerical chemistry and climate simulation system that includes submodels describing tropospheric and middle atmosphere processes and their interaction with oceans, land, and influences coming from anthropogenic emissions. It comprises the second version of the Modular Earth Submodel System (MESSy2) to link multi-institutional computer codes, in which the core atmospheric model is the fifth generation European Center Hamburg general circulation model (ECHAM5). We use a horizontal resolution of T42, with 31 hybrid vertical pressure levels up to 10 hPa (~30 km, T42L31ECMWF) and a time step of 20 minutes, with meteorology nudged to ERA5 reanalysis data as boundary conditions. AirTraf allows to calculate aircraft trajectories for given city-pairs with respect to dedicated routing strategies, considering meteorological conditions calculated by ECHAM5 online. Associated with these identified aircraft trajectories, the climate effect from aviation emissions along these trajectories is calculated from the submodel ACCF version 1.0 of EMAC. ACCF employs the aCCFs, that provide spatially and temporally resolved information on the climate effects of aviation emissions to quantify CO<sub>2</sub> and non-CO<sub>2</sub> effects. Specifically, they allow identifying regions of the atmosphere where aviation emissions induce a strong climate effect, e.g. via the formation of warming contrails or the production of radiatively active species like ozone. Thus, using these aCCFs, the estimated climate effect of aviation emissions and their spatial and temporal variability is available for the model domain: Subsequently, this is provided to AirTraf in order to enable not only estimating climate effects for calculated aircraft trajectories, but also planning of climate-optimized flight trajectories. The combination of EMAC/AirTraf/ACCF is applied here to simulate flight trajectories as great circle routes between city pairs (equal to AirClim), considering the variability of synoptic weather patterns in a continuous representation of the global atmosphere, and to quantitatively assess total climate effect and overall performance of flights.</p>
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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.