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167 results for “greenhouse gas”
An improved carbon greenhouse gas simulation in GEOS-Chem version 12.1.1
<p>The files represent all the modelled data used for the work "An improved carbon greenhouse gas simulation in GEOS-Chem version 12.1.1" by Beata Bukosa, Jenny A. Fisher, Nicholas M. Deutscher and Dylan B. A. Jones, submitted to Geoscientific Model Development (GMD), 2021.</p> <p><br> The files include:</p> <p> </p> <ul> <li>GEOS-Chem v12.1.1 source code with the new coupled simulation implemented</li> <li>The run directories for all the simulations with the specific input files defining all the setup, restart files and ATom input files</li> <li>Specific GEOS-Chem input files that are shown in the paper (i.e., OH used in all simulations)</li> <li>The output fields from all the GEOS-Chem simulations used in the analysis presented in the paper</li> <li>All the codes used for the analysis in the paper and for creating the plots</li> <li>A README file that has detailed information about all the uploaded files and directory structure</li> </ul>
Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite
<p>Scripts and results for our "Remotely Sensing River Greenhouse Gas Exchange Velocity Using the SWOT Satellite" manuscript.</p> <p>Consult the README file for a more detailed description of the data, results, and scripts.</p>
Greenhouse gas (GHG) during the Atmospheric Research Expedition to Abu Dhabi (AREAD)
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Arsenic immobilization and greenhouse gas emission depend on quantity and frequency of nitrogen fertilization in paddy soil
<p><span>Nitrogen (N) fertilization in paddy soils decreases arsenic mobility and methane emissions. However, it is unknown how quantity and frequency of N fertilization affects the interlinked redox reactions of iron(II)-driven denitrification, iron mineral (trans-)formation with subsequent arsenic (im-)mobilization, methane and nitrous oxide emissions, and how this links to microbiome composition. Thus, we incubated paddy soil from Vercelli, Italy, over 129 days and applied nitrate fertilizer at different concentrations (control: 0, low: ~35, medium: ~100, high: ~200 mg N kg<sup>-1 </sup>soil<sup>-1</sup>) once at the beginning and after 49 days. In the high N treatment, nitrate reduction was coupled to oxidation of dissolved and solid-phase iron(II), while naturally occurring arsenic was retained on iron minerals due to suppression of reductive iron(III) mineral dissolution. In the low N treatment, 40 µg L<sup>-1</sup> of arsenic was mobilized into solution after nitrate depletion, with 69% being immobilized after a second nitrate application. In the non-fertilized control, concentrations of dissolved arsenic were as high as 76 µg L<sup>-1</sup>, driven by mobilization of 36% of the initial mineral-bound arsenic. Generally, N fertilization led to 1.5-fold higher total GHG emissions (sum of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O as CO<sub>2</sub> equivalents), 158-fold higher </span><span>N<sub>2</sub>O</span><span>, and 7.5-fold lower CH<sub>4</sub> emissions compared to non-fertilization. On day 37, <em>Gallionellaceae</em>, <em>Comamonadaceae</em> and <em>Rhodospirillales</em> were more abundant in the high N treatment compared to the non-fertilized control, indicating their potential role as key players in nitrate reduction coupled to iron(II) oxidation. The findings underscore the dual effect of N fertilization, immobilizing arsenic in the short-term (low/medium N) or long-term (high N), while simultaneously increasing N<sub>2</sub>O and lowering CH<sub>4</sub> emissions. This highlights the significance of both the quantity and frequency of N fertilizer application in paddy soils. </span></p>
Unraveling the role of soil acidity alleviation strategies on greenhouse gas emissions under conventional and no-tilled system
<p>Supplementary Material </p>
Data for Greenhouse gas budgets of Central and West Asia (2000-2020)
<p>The data and code provided are utilized to support the conclusions of "Greenhouse gas budgets of Central and West Asia (2000-2020): A significant net source to the atmosphere" (submitted). The dataset comprises the processed ensemble mean values at both national and regional scales. Please note that in the dataset, "NBP" represents the NBP fluxes from TRENDY v11 models, "Wetland CH4" represents the wetland CH4 emission estimates from Terrestrial Biosphere Models in the Global Methane Budget, "Natural Soil N2O" represents the natural soil N2O emissions as estimated by NMIP2 models, and "Inversions" represents the inversion fluxes for each GHG. More detailed information about the meaning and data sources of each sector can be found in the Methods section of the manuscript and in Supplementary Information S1.</p>
Data for Greenhouse gas budgets of Central and West Asia (2000-2020)
<p>The data and code provided are utilized to support the conclusions of "Greenhouse gas budgets of Central and West Asia (2000-2020): A significant net source to the atmosphere." The dataset comprises the processed ensemble mean values at both national and regional scales. Please note that in the dataset, "TD_total" represents the inversion fluxes for each GHG, "NBP" represents the NBP fluxes from TRENDY, "Wetland_ch4" represents the wetland CH4 emission estimates from Terrestrial Biosphere Models in the Global Methane Budget, and "Soil_n2o" represents the soil N2O emissions as estimated by NMIP2 models. More detailed information about the meaning and data sources of each sector and subsector can be found in the Methods section of the manuscript and in Supplementary Information S1.</p>
Resampling code with sample data for: Eddy-covariance with slow-response greenhouse gas analyser on tall towers
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Data and code - Reducing greenhouse gas emissions from North American soybean production
<p>Database and R code for the figures and tables in the article "Reducing greenhouse gas emissions from North American soybean production", <em>Nat. Sust. </em>(2024).</p>
Dataset article "Management and restoration of Mediterranean inland saline lakes to reduce greenhouse gas emissions"
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Net greenhouse gas balance of fiber wood plantation on peat in Indonesia
<p>Tropical peatlands cycle and store globally significant amounts of carbon in their soil and biomass. Climate and land-use change alter greenhouse gas (GHG) fluxes of tropical peatlands, but the magnitude of these changes remains highly uncertain owing to limited measurements. We measured net ecosystem exchanges of carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) as well as soil nitrous oxide (N<sub>2</sub>O) fluxes between mid-2016 and mid-2022 from <em>Acacia</em> <em>crassicarpa</em> plantation, degraded forest and intact forest within the same peat landscape to represent land-cover change trajectories in Sumatra, Indonesia. Here we report the first full plantation rotation GHG balance investigation undertaken in any fiber wood plantation on peatland globally. The <em>Acacia</em> plantation was found to have lower GHG emissions than the degraded peatland, which had a similar mean groundwater level, despite more intensive land-use. The GHG emissions from the <em>Acacia</em> plantation over a full plantation rotation (38.3 ± 4.8 tCO<sub>2</sub>-eq ha<sup>−1</sup> yr<sup>−1</sup>, average ± standard deviation) were two times higher than those from the intact forest (20.1 ± 3.7 tCO<sub>2</sub>-eq ha<sup>−1</sup> yr<sup>−1</sup>), but only around half of the current IPCC Tier 1 emission factor for this land-use. Our results should help to reduce the uncertainty in the estimation of GHG emissions from globally important ecosystems, provide a complete estimate of the impact of land-use change on tropical peat, and develop science-based peatland management practices that help to minimize GHG emissions.</p>
Net greenhouse gas balance of fiber wood plantation on peat in Indonesia
<p>Tropical peatlands cycle and store large amounts of carbon in their soil and biomass<sup>1</sup><sup>-</sup><sup>5</sup>. Climate and land-use change alter greenhouse gas fluxes of tropical peatlands, but the magnitude of these changes remains highly uncertain<sup>6</sup><sup>-</sup><sup>19</sup>. Here we measure net ecosystem exchanges of carbon dioxide, methane, and soil nitrous oxide fluxes between October 2016 - May 2022 from <em>Acacia</em> <em>crassicarpa</em> plantation, degraded forest and intact forest within the same peat landscape, representing land-cover change trajectories in Sumatra, Indonesia. This allows us to present a full plantation rotation greenhouse gas flux balance in fiber wood plantation on peatland. We find that the <em>Acacia</em> plantation has lower greenhouse gas emissions than the degraded site with a similar average groundwater level, despite more intensive land-use. The greenhouse gas emissions from the <em>Acacia</em> plantation over a full plantation rotation (35.2 ± 4.7 tCO<sub>2</sub>-eq ha<sup>−1</sup> yr<sup>−1</sup>, average ± standard deviation) were around two times higher than those from the intact forest (20.3 ± 3.7 tCO<sub>2</sub>-eq ha<sup>−1</sup> yr<sup>−1</sup>), but only half of the current IPCC Tier 1 emission factor<sup>20</sup> for this land-use. Our results can help to reduce the uncertainty in greenhouse gas emissions estimates, provide an estimate of the impact of land-use change on tropical peat, and develop science-based peatland management practices as nature-based climate solutions.</p>
Data to reproduce figures for the paper "The Effect of Tropical Pacific Air-sea Coupling on the Rainfall Response to Abrupt Greenhouse Gas Forcing"
<p>Data to reproduce figures for the paper "The Effect of Air-sea Coupling over the Tropical Pacific on the Response in Rainfall to Abrupt Greenhouse Gas Forcing".</p>
Dataset for the article "Alnus viridis: an encroaching species with valuable nutritional value reducing livestock greenhouse gas emissions"
<p>Both files provide the data used for the article "<em>Alnus viridis</em>: an encroaching species with valuable nutritional value reducing livestock greenhouse gas emissions" </p> <ol> <li>"Data_file_1" provides the measured components of A. viridis, i.e. the chemical composition (micro/macro-elements, fibre fractions, ash), the phenolic content and the functional traits. </li> <li>"Data_file_2" provides the results of the in vitro measurements on organic matter digestibility and gas production.</li> </ol>
Dataset for "Responses of Soil Greenhouse Gas Fluxes to Land Management in Forests and Grasslands : A Global Meta-analysis"
<p>This dataset archives the original data for the study "Responses of Soil Greenhouse Gases Fluxes to Land Management in Forests and Grasslands: A Global Meta-analysis".</p>
Datasets for crop, soil properties and soil greenhouse gas emissions from an intercropping experiment with broccoli and fava bean
<p>Datasets with all properties measured during three crop cycles of an experiment developed to assess the efficiency of intercropping between broccoli and fava bean to enhance crop productivity, soil health and carbon sequestration and storage and reduce soil greenhouse gas emissions and the use of external inputs. </p> <p>We compared a broccoli monocrop (<em>Brassica oleracea var. italica</em> Plenck), a fava bean monocrop (<em>Vicia faba</em> L.) and different broccoli-fava bean intercropping systems in three winter crop cycles: 2018/2019, 2019/2020 and 2020/2021. The intercropping systems were: i) mixed intercropping (alternation within the same row of broccoli and fava bean plants), row intercropping 1:1 (combination of alternate rows of broccoli - fava bean) and row intercropping 2:1 (combination of two rows of the broccoli crop and one row of fava bean).</p>
Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations (Data)
<p>README file for LBL-ERA5, LBL-GCM, and band datasets used in:<br> Raghuraman et al., 2023, Geophysical Research Letters,<br> "Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations "</p> <p>Point of Contact: Shiv Priyam Raghuraman, shivr@alumni.princeton.edu</p> <p> </p> <p>LBL-ERA5</p> <p>6 files (3 experiments with olr and olr_clr output separately):</p> <p>2003-2021.GFDL.all-2010-o3_*.nc - varying WMGHG,Ts,T,q,clouds, fixed o3</p> <p>2003-2021.GFDL.fo3_*.nc - varying WMGHG and fixed Ts,T,q,clouds,surface albedo,o3</p> <p>2003-2021.GFDL.ff_*.nc - fixed Ts,T,q,clouds,surface albedo, varying o3</p> <p> </p> <p>LBL-GCM (clear-sky only)</p> <p>4 AM4 files:</p> <p>AM4piclim-control.nc (for ERF)</p> <p>AM4piclim-4xCO2_1xCO2IRF.nc (for ERF)</p> <p>AM4piclim-control_STRAT.nc (for SARF)</p> <p>AM4piclim-4xCO2_1xCO2IRF_STRAT.nc (for SARF)</p> <p>4 CM3/AM3 files:</p> <p>CTLAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>EXPAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>CTLAM3CM3_P1_2003C.nc (for IRF)</p> <p>CTLAM3CM3_P1_2021C.nc (for IRF)</p> <p> </p> <p>Band-AM4/MERRA-Total: GFDL AM4 with prescribed SSTs and sea-ice (AMIP) and nudged with MERRA winds</p> <p>2 files:</p> <p>atmos.200001-202112.olr.nc - all-sky OLR</p> <p>atmos.200001-202112.olr_clr.nc - clear-sky OLR</p> <p> </p> <p>Observational and reanalysis files used in paper (AIRS, CERES EBAF and SSF, GISTEMP, ERA5 input data) can be downloaded from their respective websites (see paper's "Open Research" section).</p> <p> </p>
Data from: Canopy soil greenhouse gas dynamics in response to indirect fertilization across an elevation gradient of tropical montane forests
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Data from: Technical note: rapid image-based field methods improve the quantification of termite mound structures and greenhouse-gas fluxes
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Data from: Treating cattle with antibiotics affects greenhouse gas emissions, and microbiota in dung and dung beetles
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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.