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140 results for “n2o”
Global soil moisture–atmosphere feedback and N2O emission dataset
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Urbanization can accelerate climate change by increasing soil N2O emission while reducing CH4 uptake
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Relative importance between nitrification and denitrification to N2O from a global perspective
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Data from: Nitrifier controls on soil NO and N2O emissions in three chaparral ecosystems under contrasting atmospheric N inputs
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Data from: Distinct N-cycling microbial communities contribute to microtopographic variation in soil N2O emissions
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Biochar increases tree biomass in a managed boreal forest, but does not alter N2O, CH4, and CO2 emissions
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Data from: Rapid nitrate reduction produces pulsed NO and N2O emissions following wetting of dryland soils
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Soil N2O and NO emissions from an arid, urban ecosystem in central Arizona-Phoenix
Soil nitrogen (N) cycling and fluxes of N2O and NO in three land-use types across the metropolitan area of Phoenix, Arizona has been measured.Urbanization increased N2O emissions compared to native landscapes, primarily due to the expansion of fertilized and irrigated lawns. Fluxes of N2O from lawns ranged from 18 to 80 mg N m^(-2) h^(-1) and were significantly larger than managed xeric landscapes (2.5-22 mg N m^(-2) h^(-1)) and remnant desert sites within the urban core (3.7-14 mg N m^(-2) h^(-1)). In contrast, average NO fluxes from lawns were not significantly different from native desert when dry (6-80 mg N m^(-2) h^(-1); 5-16 mg N m^(-2) h^(-1) desert) and were lower than fluxes from deserts after wetting events. Furthermore, urbanization has significantly altered the temporal dynamics of NO emissions by replacing pulse-driven desert ecosystems with year-round irrigated, managed lawns. Short-term, pulse-driven emissions of NO from wetting of dry desert soils may reach 35% of anthropogenic emissions within a day after summer monsoon storms. If regional O3 production is NOx-limited during the monsoon season, fluxes from warm, recently wet arid soils may contribute to summer O3 episodes. .
Comparison of different gas extraction techniques to analyze CH4 and N2O compositions in gas trapped in permafrost ice wedges
<p>Methane (CH4) and nitrous oxide (N2O) compositions in ground ice may provide information on their production mechanisms in permafrost. However, existing gas extraction methods have not been well tested. We tested conventional wet and dry gas extraction methods using ice wedges from Alaska and Siberia, finding that both methods can extract gas from the easily extractable parts of the ice (e.g., gas bubbles), and yield similar results for CH4 and N2O mixing ratios. We also found insignificant effects of microbial activity during wet extraction. However, both techniques were unable to fully extract gas from the ground ice, presumably because gas molecules adsorbed onto or enclosed in soil aggregates are not easily extractable. Estimation of gas production in subfreezing environment of permafrost should consider such incomplete gas extraction.</p>
Nitrate removal and N2O production from upflow and downflow column woodchip bioreactors
<p class="ParaText"><span>Woodchip denitrifying bioreactors (WDBR) reduce off-field tile drainage nitrogen (N) losses from agricultural fields. Limited evaluation exists regarding the influence of flow direction through WDBRs. <a name="_Hlk40339771">Changing flow direction could reduce short circuiting. </a> This study evaluated the dependency of nitrate-nitrogen removal and dissolved nitrous oxide (<i>d</i>N<sub>2</sub>O) production rates on vertical flow direction in triplicate column bioreactors at 12-h (without carbon dosing) and 2-h (with carbon dosing) hydraulic residence times. Results presented demonstrate that there was no significant difference in overall nitrogen removal rates from these column bioreactors as a function of flow direction. There was the suggestion of lower nitrous oxide (N<sub>2</sub>O) production in the downflow direction, although this was not statistically significant due to the high variability of the N<sub>2</sub>O production observed in the upflow direction. <a name="_Hlk43820284">Carbon addition led to bioclogging of downflow columns; future work needs to identify dosing rate, placement, and conditions that prevent biofilm formation.</a></span></p>
Data from: Machine learning improves predictions of agricultural nitrous oxide (N2O) emissions from intensively managed cropping systems
<p><span>The potent greenhouse gas nitrous oxide (N</span><sub><span>2</span></sub><span>O) is accumulating in the atmosphere at unprecedented rates largely due to agricultural intensification, and cultivated soils contribute ~60% of the agricultural flux. Empirical models of N</span><sub><span>2</span></sub><span>O fluxes for intensively managed cropping systems are confounded by highly variable fluxes and limited </span><span><span>geographic coverage;</span></span><span> process-based biogeochemical models are rarely able to predict daily to monthly emissions with > 20% accuracy even with site-specific calibration. Here we show the promise for machine learning (ML) to significantly improve field-level flux predictions, especially when coupled with a cropping systems model to simulate unmeasured </span><span><span>soil</span></span><span> parameters. We used sub-daily N</span><sub><span>2</span></sub><span>O flux data from six years of automated flux chambers installed in a continuous corn rotation at a site in the upper U.S. Midwest (~3000 sub-daily flux observations), supplemented with weekly to biweekly manual chamber measurements (~1100 daily fluxes), to train an ML model that explained 65-89% of daily flux variance with very few input variables –soil moisture, days after fertilization, soil texture, air temperature, soil carbon, precipitation, and N fertilizer rate. When applied to a long-term test site not used to train the model, the model explained 38% of the variation observed in weekly to biweekly manual chamber measurements from corn, and 51% upon coupling the ML model with a cropping systems model that predicted daily soil N availability. </span><span><span>This represents a 2-3 times improvement over conventional process-based models and with substantially fewer input requirements.</span></span><span> This coupled approach </span><span><span>offers promise</span></span><span> for better predictions of agricultural N</span><sub><span>2</span></sub><span>O emissions and thus more precise global models and more effective </span><span><span>agricultural mitigation interventions.</span></span></p>
Observed monthly N2O emission dataset used for model carlibaration and validation
<p>The N<sub>2</sub>O emission dataset for calibration sites was extracted from the published figures and tables using GetData Graph Digitizer version 2.24; the other information such as biome, geographic location, experimental period, soil organic carbon content, soil pH and soil texture was selected from corresponding literature. If the data related to soil was not avaliable, we extracted them from the soil database(IGBP-DIS)</p>
Hydrologic Connectivity Regulates Riverine N2O Sources and Dynamics [Dataset]
<p>This repository contains summarized N2O concentration, isotope, watershed attribute, and stream hydraulics data for the Cannon River Watershed. More details about the data can be found in the enclosed metadata file.</p>
Database for N2O emissions after EOM application
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Combined CH4, N2O and CO2 fluxes budgets reveal a net carbon sink across a glacier-ocean continuum
<p>This dataset is supplument to a manuscript "Meltwater impacts CH4 and N2O fluxes across a glacier-ocean interface". </p> <p>Dataset includes </p> <ul> <li>timeseries.xlsx <ul> <li>A timeseries dataset conducted at Jökulsárlón Lagoon in Iceland. It includes CH<sub>4</sub> and N<sub>2</sub>O concentration, water flow and environmental variables. </li> </ul> </li> <li>discrete_v3.xlsx <ul> <li>Discrete samples conducted around Jökulsárlón Lagoon in Iceland It includes CH<sub>4</sub> and N<sub>2</sub>O concentration, nutrient. </li> <li>Add lat and lon (updated: 20 Nov 2024) </li> </ul> </li> </ul>
N2O flux data at Lake Suwa
<p>N2O emissions from Lake Suwa were observed with the floating-chamber technique. The dataset also includes meteorological and limnological variables.</p>
MIROC4-ACTM N2O inversion fluxes (1997-2019)
<p>As described in</p> <p>Patra, P. K., E. J. Dlugokencky, J. W. Elkins, G. S. Dutton,. Y. Tohjima, M. Sasakawa, A. Ito, R. F. Weiss, M. Manizza, P. B. Krummel, R. G. Prinn, S. O'Doherty, D. Bianchi, C. Nevison, E. Solazzo, H. Lee, S. Joo, E. A. Kort, S. Maity, and M. Takigawa, 2022: Forward and inverse modelling of atmospheric nitrous oxide using MIROC4-atmospheric chemistry-transport model.<em> J. Meteor. Soc. Japan</em>, <strong>100</strong>,<br> <a href="https://doi.org/10.2151/jmsj.2022-018">https://doi.org/10.2151/jmsj.2022-018.</a></p>
Data-set of CO2, CH4, N2O dissolved concentrations and ancillary data in surface waters of 24 African lakes.
<p>Geo-referenced and timestamped data-set of water temperature, Specific conductivity (SpCond), oxygen saturation level (%O<sub>2</sub>), dissolved methane (CH<sub>4</sub>) concentration, dissolved nitrous oxide (N<sub>2</sub>O) concentration, partial pressure of carbon dioxide (pCO<sub>2</sub>), carbon stable isotope composition of dissolved inorganic carbon (δ<sup>13</sup>C-DIC), dissolved organic carbon (DOC) concentration, chlorophyll-a (Chl-a) concentration, cyanobacteria abundance (CHEMTAX), nitrate (NO<sub>3</sub><sup>-</sup>) and ammonia concentration (NH<sub>4</sub><sup>+</sup>), coloured dissolved organic matter slope ratio (CDOM SR) in surface waters of African 24 lakes (Victoria, Tanganyika, Albert, Kivu, Edward, Mai Ndombe, Tumba, George, Kamohonjo, Alaotra, Ndalaga, Nyamusingere, Kyamwinga, Mbita, Lukulu, Yandja, Mbalukira, Nkugute, Nyamunuka, Kitagata, Mrambi, Kyashanduka, Katinda, Lac Vert).</p>
N2O production and denitrificaion rate in the Plastisphere and bulk water
<p>The data presented here represent the raw data of some indicators from plastisphere and bulk water. The data include C-D ratios, lipids/fatty acids intensities, EPS, c-di-GMP, N2O production, denitrification rate, percentage, isotope ratios, microbial communities. The plastisphere includes four types of plastics, PE, PP, PS and PVC.</p>
a N2O dataset collecting from WEST software
<p>This dataset was collected from WEST. The simulation is for an activated sludge process.</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.