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223 results for “ammonia”
Seasonal Distribution of Ammonia-Oxidizing Archaea and Ammonia-Oxidation Rates in the South Atlantic Bight from April to November 2014
Previous work in nearshore waters of the Georgia USA coast has demonstrated mid-summer peaks in the abundance of Thaumarchaeota (blooms with 100 to 1,000-fold increases) accompanied by spikes in nitrite concentration. These studies were performed at one location, so the areal extent of the bloom is unknown, nor has it been demonstrated conclusively that it develops in inshore waters. We collected data on rates of ammonia oxidation and the distribution of Thaumarchaeota, ammonia-oxidizing Betaproteobacteria (AOB), nitrite-oxidizing Nitrospina and environmental variables during 6 cruises aboard the UNOLS vessel R/V Savannah from April to November 2014 on transects of the South Atlantic Bight to evaluate the areal extent and timing of the bloom. This data set includes measurements of Chlorophyll-a concentration, PAR attenuation coefficient, oxygen concenrations, temperature, salinity and nitogenous nutrient concentrations (nitrite, nitrite + nitrate, ammonium, urea), and estimates of Archaea, bacteria and diatom gene concentration based on quantitative PCR.
Coupling between Sediment and Water Column Populations of Ammonia Oxidizing Thaumarchaeota in the Duplin River near Sapelo Island, Georgia
Populations of nitrifying organisms in the water column at Marsh Landing display a midsummer peak in the abundance of ammonia oxidizing Archaea (AOA) at the site, coinciding with a peak in nitrite concentration. Marsh Landing is at the mouth of the Duplin River, a dead-end tidal channel that drains an extensive area of salt marsh. While the lower Duplin River at Marsh Landing exchanges tidally with Doboy Sound and thus South Atlantic Bight (SAB) coastal waters, water in its upper reaches has a residence time of weeks. The work reported here had two goals: 1) test the hypothesis that the surrounding salt marsh is the source of nitrifiers seen in water samples taken at Marsh Landing; and 2) compare the seasonal dynamics of nitrifiers in surficial sediments with those in the water column. We sampled 6 stations along the ~20 km length of the Duplin River. We collected surface water samples (~0.20 m) at low- to mid-tide, monthly from April-December 2014. Sediment samples (top 1 cm) were collected at the same time from unvegetated creek bank at 2 locations on the Duplin River and from 4 locations spanning the creek bank-to-upland gradient of the saltmarsh accessible from the Teal Boardwalk. The abundance of ammonia oxidizing Archaea, Marine Group 1 Archaea (Thaumarchaeota), ammonia oxidizing Betaproteobacteria (AOB), Bacteria and Nitrospina, a nitrite oxidizing bacterium, were determined by quantitative PCR (qPCR) of DNA extracted from the samples. This data set contains the abundance estimates from April to December 2014 for sediment and water column samples, with corresponding water quality measurements (temperature, salinity and nitrogenous nutrient concentrations).
Porewater measurements of dissolved nutrients (ammonia, nitrate/nitrite, phosphate) from core monitoring sites in the GCE-LTER domain following hurricane Irma from October 2017 to October 2018.
To access the effect of hurricane Irma on the GCE domain, porewater samples were collected to evaluate porewater nutrient concentrations at four core GCE monitoring sites (7, 8, 9 and 11). A limited number of samples were collected in October 2017 (a month after the storm surge from hurricane Irma hit the east coast of the United States) and then all sites were sampled in Nov 2017 and in Jan, Feb, Apr and Oct 2018. Porewater samples were obtained from approximately 10 cm depth using Rhizon samplers and then analyzed for ammonium, nitrate + nitrite, and phosphate concentrations.
Global ammonia emissions from CAMEO throughout the century for 3 scenarios (2000-2100)
<p><strong>Global ammonia emissions from the CAMEO process-based model </strong>(general model description and evaluation can be found in Beaudor et al., 2023, GMD; https://doi.org/10.5194/gmd-16-1053-2023).</p><p>Monthly files containing global NH3 emissions and Manure application rates in gN.m2.yr-1 (2.5° lon x 1.27° lat; IPSL-CM6A-LR Earth System Model resolution):</p><p>1) total agricultural emissions (TOT_AGRI; the sum of manure management and agricultural soil emissions)</p><p>2) manure management emissions (MANURE_MANAG.)</p><p>3) agricultural soil emissions (SOIL_AGRI)</p><p>4) natural soil emissions (SOIL_NAT) corrected for baresoil (excluding Sahara in this new version)</p><p>5) Fraction of continent (CONT_FRAC) from the model to use for CTM prescription or global budget calculation</p><p>6) TAN and non TAN applied to grassland from ruminants during grazing (tan_input_graz, nontan_input_graz)</p><p>7) TAN and non TAN applied to grassland from ruminants and considered as fertilizers (tan_input_manureApp_grass, nontan_input_manureApp_grass)</p><p>8) TAN and non TAN applied to cropland from all types of animal and considered as fertilizers (tan_input_manureApp_crop, nontan_input_manureApp_crop)</p><p>9) Grazing intensity (grazing_intensity, unitless)</p><p>10) Net Primary Production of grassland and grass biomass dedicated to livestock feed (NPP_grass, Cgrass_ingested in gC.m2.yr-1)</p><p>The four files correspond to a specific simulation using input4MIPs forcing files :</p><p>- Present-day simulation from 2000 to 2014 </p><p>- Future simulation from 2015 to 2100 under scenario SSP-2.45</p><p>- Future simulation from 2015 to 2100 under scenario SSP-4.34</p><p>- Future simulation from 2015 to 2100 under scenario SSP-5.85</p><p>Note that these datasets have been prepared in the scope of a publication to be submitted.</p><p><i><strong>Beaudor, M., N. Vuichard, J. Lathière, D. Hauglustaine., Historical and future ammonia emissions database (2000-2100) from the CAMEO process-based model, in preparation.</strong></i></p>
The ALFAM2 dataset on ammonia loss from field-applied manure
<p>The ALFAM2 database has measurements of ammonia volatilization (emission) from field-applied liquid animal manure (slurry). The dataset consists of two files: one with plot- (<code>ALFAM2_plot.csv</code>) and one with measurement interval-level (<code>ALFAM2_interval.csv</code>) observations. For information on file headers (column names), see the <code>*-level_variables.csv</code> files. The two data files can be merged on two plot keys (identification codes): <code>pid</code> and <code>pmid</code>. See the <a href="https://github.com/sashahafner/ALFAM2-data/blob/master/README.md">README.md</a> file in the GitHub repository at <a href="https://github.com/sashahafner/ALFAM2-data">https://github.com/sashahafner/ALFAM2-data</a>, the web page <a href="https://projects.au.dk/alfam//">https://projects.au.dk/alfam/</a> (or <a href="http://alfam.dk">alfam.dk</a>), and the reference and related identifiers here on the Zenodo page for more details. The ALFAM2-data GitHub repository also has original submissions from data contributors along with scripts necessary for processing the data to create the dataset shown here. Each Zenodo version can be matched to the GitHub versions through the release tags (see the releases page for a list: https://github.com/sashahafner/ALFAM2-data/releases)</p>
Environmental and economic potential of decentralised electrocatalytic ammonia synthesis powered by solar energy
<p>Dataset associated with the publication "Environmental and economic potential of decentralised electrocatalytic ammonia synthesis powered by solar energy" by Sebastiano C. D'Angelo, Antonio J. Martín, Selene Cobo, Diego Freire-Ordóñez, Gonzalo Guillén-Gosálbez, and Javier Pérez-Ramírez, available at <a href="https://doi.org/10.1039/D2EE02683J">https://doi.org/10.1039/D2EE02683J</a>. The dataset includes the numeric data required to plot all the figures embedded in the main manuscript and in the Electronic Supplementary Information (ESI).</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>GeneralParameters</strong>: numerical values for the scaled functional unit used in the study, the world population value adopted, and the three voltage efficiencies assumed in different parts of the study.</li> <li><strong>AL_BaseCase_SensECE</strong>: numerical values associated with the results for the ammonia leaf scenarios adopting a voltage efficiency of 63% (base case) and a Faradaic efficiency varying from 1% to 100%; highest, average, and lowest capacity factors for the solar power production were here used. The ammonia leaf configuration here assessed is the one including solar panels, electrolyzer, and fuel cell as key components. The results report all the ReCiPe 2016 (hierarchical approach) midpoints and endpoints and the values for the assessed planetary boundaries; the levelised cost of ammonia (LCOA) is reported, as well.</li> <li><strong>AL_EtaV75_SensECE</strong>: this sheet has the structure as the previous one, but includes the results for the ammonia leaf scenario using 75% voltage efficiency, instead of 63%. The remaining assumptions do not deviate from the base case.</li> <li><strong>AL_Eta100_SensECE</strong>: this sheet has the structure as the previous one, but includes the results for the ammonia leaf scenario using 100% voltage efficiency, instead of 63%. The remaining assumptions do not deviate from the base case.</li> <li><strong>AL_NoFC_H2Vented_SensECE</strong>: this sheet has the same structure as the sheet "AL_BaseCase_SensECE", but includes the ammonia leaf scenario using a configuration with no fuel cell. The hydrogen by-product was here considered vented to the air. The remaining assumptions do not deviate from the base case.</li> <li><strong>AL_NoFC_H2Subst_SensECE</strong>: this sheet has the same structure as the sheet "AL_BaseCase_SensECE", but includes the ammonia leaf scenario using a configuration with no fuel cell. The hydrogen by-product was here considered substituting the production of an equivalent quantity from a water electrolyzer deployed in the same location as the ammonia leaf. The remaining assumptions do not deviate from the base case.</li> <li><strong>AL_BaseCase_SpatAnal_BreakFEff</strong>: numerical results for the ammonia leaf base case scenario stemming from the spatial analysis performed on a global grid of 1140 points. The yearly average capacity factors for the solar panels at each location are included, and the results portraying the breakeven Faradaic efficiency for the indicators climate change - CO<sub>2</sub> concentration, global warming, human health, and levelised cost of ammonia were included. The assumptions for the voltage efficiency and the other parameters correspond to the base case.</li> <li><strong>AL_BaseCase_SpatAnal_AbsValues</strong>: numerical results for the ammonia leaf scenarios using the base case state-of-the-art (34%) and 100% Faradaic efficiency, as well as the base case voltage efficiency of 63%. The same metrics as the previous sheet are reported. The structure of the sheet is the same as the previous one.</li> <li><strong>AL_BaseCase_Breakdowns</strong>: breakdown of the same four indicators as the previous sheet for the best and worst combination of Faradaic efficiency and solar panels capacity factors, i.e., 34% Faradaic efficiency and 6% capacity factor on one side and 100% Faradaic efficiency and 26% capacity factor on the other side. The breakdown is divided into solar panels, electrolyser, fuel cell, and other elements. A further breakdown of the levelised cost of ammonia (LCOA) into capital expenditure (CAPEX) and operating expenditure (OPEX) is provided, as well. The voltage efficiency is the same as the base case, as well as the other parameters.</li> <li><strong>AL_BaseCase_CAPEXSens</strong>: numerical results for the levelised cost of ammonia (LCOA) in dependence of the sensitivity on the capital expenditure (CAPEX) for the ammonia leaf configuration assessed in the base case. Two cases assuming state-of-the-art (34%) and 100% Faradaic efficiency were assumed, and lowest, average, and highest capacity factor are included. The remaining parameters do not deviate from the base case configuration.</li> <li><strong>AL_gHB_BestMap</strong>: numerical results to produce the map showing the best technology between ammonia leaf (AL) and green Haber-Bosch (gHB) in the category climate change - CO<sub>2</sub> concentration for all the assessed locations. column D shows the share of safe operating space (%SOS) for each location, while column E shows which technology was selected, where 1 is ammonia leaf and 2 is green HB.</li> <li><strong>AL_BaseCase_Sensitivity</strong>: percentual variation of the results obtained assuming the base configuration ammonia leaf for a state-of-the-art Faradaic efficiency and an average capacity factor for the solar panels. The varied parameters include the voltage efficiency (columns C-D-E), the levelised cost of electricity (columns G-H-I), the electrolyser cost (columns K-L-M), the fuel cell cost (columns O-P-Q), the electrolyser environmental impact (columns S-T-U), and the fuel cell environmental impact (columns W-X-Y).</li> <li><strong>CompTech_BaseCase</strong>: environmental and economic metrics characterizing the assessed Haber-Bosch scenarios (business as usual, BAU; blue Haber-Bosch; green Haber-Bosch for lowest, average, and highest solar panels capacity factor; BAU assuming natural gas spot prices in Europe in August 2022). The reported metrics are the ReCiPe 2016 (hierarchical approach) midpoints and endpoints, the planetary boundaries, and the levelised cost of ammonia (LCOA).</li> <li><strong>CompTech_EtaV75</strong>: this sheet has the same structure as the previous one, but the hydrogen electrolyser used for the green Haber-Bosch scenarios was assumed to have a 10% stack efficiency improvement. The remaining parameters are the same.</li> <li><strong>CompTech_EtaV100</strong>: this sheet has the same structure as the previous one, but the hydrogen electrolyser used for the green Haber-Bosch scenarios was assumed to have a 100% stack efficiency. The remaining parameters are the same.</li> <li><strong>CompValues_Fig1</strong>: numerical values for yearly global warming impacts of a selection of countries, as well as for the yearly human health impacts of selected diseases and catastrophic events.</li> </ul> <p> </p>
Planetary Boundaries Assessment of Flue Gas Valorization into Ammonia and Methane
<p>Dataset associated with the publication "Planetary Boundaries Assessment of Flue Gas Valorization into Ammonia and Methane" by Sebastiano C. D'Angelo, Julian Mache, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1021/acssuschemeng.1c01915">https://doi.org/10.1016/B978-0-323-95879-0.50134-X</a>. The dataset includes the numeric data associated with Table 1 and Figure 2, converted into a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>StreamTable</strong>: numerical values associated with full set of streams depicted in Figure 1, among which a selection is reported in Table 1.</li> <li><strong>LCA-Results</strong>: numerical values associated with the breakdown of the environmental impacts for the selection of scenarios reported in Figure 2, for all the assessed control variables.</li> </ul>
Planetary Boundaries Analysis of Low-Carbon Ammonia Production Routes
<p>Dataset associated with the publication "Planetary Boundaries Analysis of Low-Carbon Ammonia Production Routes" by Sebastiano C. D'Angelo, Selene Cobo, Abhinandan Nabera, Antonio J. Martín, Javier Pérez-Ramírez, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1021/acssuschemeng.1c01915">https://doi.org/10.1021/acssuschemeng.1c01915</a>. The dataset includes the numeric data required to plot all the figures embedded in the main manuscript and in the Supporting Information (SI), as well as the tables presented in the SI converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>LCA-Total</strong>: numerical values associated with the total share of safe operating space for all the assessed control variables of the seven planetary boundaries quantified in the study, for all the considered scenarios. The results are presented for the three different downscaling approaches considered in the study. The global warming impacts for all the scenarios, calculated with the ReCiPe 2016 methodology (hierarchist approach), are here reported, as well.</li> <li><strong>LCA-Breakdown</strong>: numerical values associated with the breakdown of the environmental impacts for the selection of scenarios reported in the main manuscript, for all the assessed control variables.</li> <li><strong>Economics</strong>: numerical values associated with the breakdown of the economic impacts reported in the main manuscript, for all the assessed scenarios.</li> <li><strong>SI-Tables-LCI</strong>: tables reported in the SI associated with the environmental assessment of all the scenarios.</li> <li><strong>SI-Tables-Economics</strong>: tables reported in the SI associated with the economic assessment of all the scenarios.</li> </ul>
Air-Sea Ammonia Fluxes Calculated from High-Resolution Summertime Observations Across the Atlantic Southern Ocean
<p>This data set includes ocean ammonium concentrations, atmospheric ammonia gas concentrations, and calculated air-sea ammonia fluxes from the Atlantic sector of the Southern Ocean during summer. Associated with the folloiwng paper: </p> <p> https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020GL091963</p>
Replication data for: Energy flow analysis of an industrial ammonia refrigeration system
<p>This dataset includes energy data acquired from a pelagic fish processing plant, including data from an industrial ammonia refrigeration system that provides cooling and freezing. In addition, production data is included. Data from the system was analysed within the KSP project PCM-STORE (308847) supported by the Research Council of Norway and industry partners. PCM-STORE aims at building knowledge on novel PCM technologies for low-temperature thermal energy storage. Collecting and analysing data is an important part of evaluating the potential for reduction of CO2 emissions and increasing energy efficiency. Many processing plants measure and log data, but it is not often published. This dataset includes specific energy demand, peak power demand, power demand for different sections of the plant, ambient temperatures, and production volumes. The data was collected in 2021. The included graphics show the refrigeration system and some resulting tables and graphs. Production follows a seasonal cycle throughout the year, with no (or very low) production in the spring (Mar-May), and peak production in the autumn (Sep-Nov). The cycle is linked to the seasonal availability of fish. Annual SEC numbers (200-247 kWh/tonnes) were found to be in line with other Norwegian pelagic plants. A strong dependency between SEC and volume throughput were also found, where months of low production resulted in high SEC values and vice versa. Knowledge about the processes indicates that a fillet production is more energy intensive compared to round production, due to more energy demand from the fillet sections, higher mass (fish and brine) in each box and higher requirement of hot water for cleaning. This dataset is related to the conference paper "Energy flow analysis of an industrial ammonia refrigeration system and potential for a cold thermal energy storage" presented at the 15th IIR Gustav Lorentzen Conference on Natural Refrigerants, Trondheim, Norway 13-15 June 2022.</p>
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model : Model Ouput Data
<p>This upload includes data associated with the manuscript "Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model : )" submitted to Geoscientific Model Development. The dataset includes an output file with the simulated ammonia emissions for the agricultural sector.</p> <p>The emissions (manure management and soil), manure production and soil ammonium concentrations are monthly fields from the simulation for 2007-2015.</p> <p>Additional information is given in the readme file</p>
Estimating global ammonia (NH3) emissions based on IASI observations from 2008 to 2018
<p>The dataset ia produced based on the Infrared Atmospheric Sounding Interferometer (IASI) observations in Luo et al.,(2022), by updating the prior ammonia (NH3) emission fluxes with the ratio between biases in simulated NH3 concentrations and effective NH3 lifetimes against the loss of the NHx family (NHx ≡ NH3 + NH4+). We then include sulfur dioxide (SO2) column to correct the NH3 emission trends over India and China, where SO2 emissions have changed rapidly in recent years. Finally, we quantify the uncertainty of NH3 emission by a series of perturbation and sensitivity experiments. The GEOS-Chem simulation driven by top-down estimates has lower bias with the IASI observations than prior emissions, demonstrating the consistency of our estimates with observations.</p>
Electronic Supporting Information for Catalytic Ammonia Oxidation to Dinitrogen by a Nickel Complex
<p>The dataset provides electronic supporting information in the format of XYZ molecular files, formatted Gaussian checkpoint files, and cube files for atomic spin density distributions for selected complexes obtained while investigating the catalytic mechanism of ammonia oxidation to dinitrogen using a N-heterocyclic carbene containing nickelocene complex.</p> <p>The level of theory used for all calculations is omega-B97xD with def2TZVP basis set. All calculations were performed using the Gaussian16 suite of programmes.</p> <p><strong>Model Set 1</strong> contains the metal free compounds and were used to calculate the overall thermodynamics of the ammonia oxidation reaction.</p> <p><strong>Model Set 2</strong> corresponds to the most truncated, in vacuo optimized structures.</p> <p><strong>Model Set 3</strong> comprises from non-truncated, realistic structures embedded in polarizable continuum model of benzene.</p> <p> </p>
Elbrus Ice Core, Caucasus record of ammonia (NH4+)
<p><span>A deep ice core was drilled to bedrock (182.6 m) in 2009 on the western plateau of <span>Mount Elbrus </span>(ELB, 43°N, 42°E; 5115 m above sea level, asl) in the Caucasus (Russia).</span><span> </span><span>The upper 168.6 m (131.5 meters</span><span> </span><span>water equivalent, mwe) depth of the ice core were first dated by annual layer counting using pronounced seasonal variations in ammonium and succinate concentrations, both exhibiting well-marked winter minima (Mikhalenko et al., 2015; Preunkert et al., 2019). <span>Chemical measurements were done with a Dionex ICS-1000 chromatograph equipped with a CS12 separator column for cations </span>(Na<sup>+</sup>, K<sup>+</sup>, Mg<sup>2+</sup>, Ca<sup>2+</sup>, and NH<sub>4</sub><sup>+</sup>), a Dionex 600 equipped with an AS11 separator column for anions (Cl<sup>-</sup>, NO<sub>3</sub><sup>-</sup>, and SO<sub>4</sub><sup>2-</sup>) and light carboxylates. Detailed working conditions are given in Legrand et al. (2013). <span>Using the winter ammonium/succinate minima we determined half-year summer and winter means of of ammonia (NH4+) from 1748 to 2009.</span></span></p>
Dataset and code: One-tenth of EU's biomethane potential combined with carbon capture and storage can shift the region's ammonia production to net-zero
<h2>Overview</h2> <p>Repository to share the data and code associated with the scientific article <strong>Istrate et al. One-tenth of EU’s biomethane potential combined with carbon capture and storage can shift the region’s ammonia production to net-zero. One Earth (2024)</strong>. The repository contains data files and code to import the life cycle inventories (LCIs), reproduce the results, and generate the figures presented in the article.</p> <div> <h2>Repository structure</h2> </div> <p>The data folder includes:</p> <ul> <li><code>inventories.xlsx</code> contains the LCI datasets for biomethane and ammonia production formatted for use with <a href="https://github.com/brightway-lca">Brightway</a>.</li> <li><code>sustainable_biomethane_potential_Europe.xlsx</code> contains data on the sustainable biomethane potential in Europe disaggregated by feedstock and country.</li> <li><code>ammonia_production_europe.xlsx</code> contains ammonia production levels in the EU in 2021.</li> <li><code>SA_methane leakage_for presample.xlsx</code> contains data to perform sensitivity analysis on the methane leakage with <a href="https://github.com/PascalLesage/presamples">presamples</a></li> <li><code>SA_upgrading technology_presamples.xlsx</code> contains data to perform sensitivity analysis on upgrading technologies with <a href="https://github.com/PascalLesage/presamples">presamples</a></li> <li><code>results</code> folder within data contains csv files with the results, which are used in <code>05_visualization.ipynb</code> for analysis and visualization purposes.</li> </ul> <p>The notebooks folder includes:</p> <ul> <li><code>01_project_setup.ipynb</code> sets up a new Brightway project and imports the ecoinvent database.</li> <li><code>02_lci.ipynb</code> imports the LCIs and regionalize some datasets (e.g., biomethane supply based on the bimethane potential).</li> <li><code>03_lcia.ipynb</code> calculates life cycle impacts and all the additional results presented in the paper (e.g., calculation of blending ratios).</li> <li><code>04_sensitivity_analysis.ipynb</code> performs the sensitivity analysis.</li> <li><code>05_visualization.ipynb</code> imports all results and generates the figures presented in the scientific article.</li> </ul> <p>The src folder contains supporting functions required to regionalize LCIs and perform the calculations.</p> <div> <h2>How to get propertary data</h2> </div> <p>Some of the LCI datasets in the <code>inventories.xlsx</code> file are partially based on data from the ecoinvent LCI database. To comply with licensing requirements, the file shared in this repository does not include these data points. If you hold a valid ecoinvent license, please contact me directly to receive the full input files containing all ecoinvent data points.</p> <h2>Contact</h2> <p>Robert Istrate: i.r.istrate@cml.leidenuniv.nl</p>
Gridded ammonia emission inventory in mainland China
<p>We produce and provide an improved ammonia emission inventory in mainland China in 2016. The emission inventory have been developed with 1/12 by 1/12 degree spatial resolution. The unit of the emission inventory is t/grid/year. </p>
Thermodynamic properties of ammonia-water (NH3H2O mixture). In Esperanto
<p>Thermodynamic data for the ammonia-water mixture are adapted from: Ibrahim, O. M. (1993). Thermodynamic properties of ammonia-water mixtures. In ASHRAE Transactions: Symposia (Vol. 93, p. 1495). <br> <br> </p>
Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling
<p>The set consists of 5 files that constitute the main calculations of ammonia emissions over Europe for the years 2013-2020. <br> The detailed description of variables follows:</p> <p>1) PriorEmission.nc<br> - Pall: tensor of the size 240 x 200 x 12 x 8 (lat x lon x months x years) with ammonia prior emissions used in the study [ng/m2/s]</p> <p>2) PosteriorEmission.nc<br> - Xall: tensor of the size 240 x 200 x 12 x 8 (lat x lon x months x years) with ammonia posterior emissions [ng/m2/s]</p> <p>3) UncertaintyEmission.nc<br> - Uall: tensor of the size 240 x 200 x 12 x 8 (lat x lon x months x years) with uncertainty of posterior emissions [ng/m2/s]</p> <p>4) stations_vmodVSobs.mat <br> - st_list: list of stations identifiers, 53 stations in total<br> - st_coord: stations coordinates [lot,lat]<br> - st_OBSdays: matrix of the size 53 x (366*8) with observations in daily resolution [ug/m3]<br> - st_ind_obs: logical matrix of the size 53 x (366*8) with indicators when each station provides observation (1) and when not (0)<br> - st_prior_vmod_days: matrix of the size 53 x (366*8) with calculated concentrations using model with prior emission [ug/m3]- st_post_vmod_days: matrix of the size 53 x (366*8) with calculated concentrations using model with posterior emission [ug/m3]<br> - st_prior1_vmod_days: same as st_prior_vmod_days for EC6G4 prior<br> - st_prior2_vmod_days: same as st_prior_vmod_days for EGG prior<br> - st_prior3_vmod_days: same as st_prior_vmod_days for NE prior<br> - st_prior4_vmod_days: same as st_prior_vmod_days for VD prior</p>
Ammonia emissions from a wastwater treatment plant
<p>These data contain ammonia concentration measurements using line-integrated miniDOAS instruments and emission calculations using an inverse dispersion method applying the bLS model at a wastewater treatment plant during several weeks in September and October 2019 in Switzerland. The data are described in a manuscript titled "Ammonia emissions from a dairy housing and wastewater treatment plant quantified with an inverse dispersion method accounting for deposition loss" submitted to the Journal of Air & Waste Management in 2023.</p> <p>These measurements were funded by the Swiss Federal Office for the Environment (Contract 06.0091.PZ / R281-0748).</p>
Ammonia emissions from a Swiss dairy housing
<p>These data contain ammonia concentration measurements using line-integrated miniDOAS instruments and emission calculations using an inverse dispersion method applying the bLS model at an experimental dairy housing operated by Agroscope in Tänikon, Switzerland during several months from September to December 2018. The data are described in a manuscript titled "Ammonia emissions from a dairy housing and wastewater treatment plant quantified with an inverse dispersion method accounting for deposition loss" submitted to the Journal of Air & Waste Management in 2023.</p> <p>These measurements were funded by the Swiss Federal Office for the Environment (Contract 00.5082.P2I R254-0652).</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.