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4,775 results for “carbon”
Carbon storage in old hedgerows: The importance of below-ground biomass
<p>Dataset to the manuscript: Drexler, S., Thiessen, E., & Don, A. (2023). Carbon storage in old hedgerows: The importance of below-ground biomass. GCB Bioenergy. https://doi.org/10.1111/gcbb.13112</p><ul><li>Drexler_et_al_2023-cn_biomass: contains the data on the biomass C/N measurements</li><li>Drexler_et_al_2023-overallstocks: contains the calculated carbon stocks per subplot for all carbon pools</li><li>Drexler_et_al_2023-soc_cropland: contains the calculated soil organic carbon stocks (0-100cm soil depth) of the reference cropland</li><li>Drexler_et_al_2023-soc_weight_fine_roots: contains the raw data on the dry weight of the fine roots and the raw data on the soil samples (C/N data, dry weight, stone/root fraction) per subplot and sampling depth</li><li>Drexler_et_al_2023-weight_above_ground_biomass: contains the raw data on the dry weight of the harvestable biomass and biomass of the mature trees per subplot</li><li>Drexler_et_al_2023-weight_coarse_roots_litter: contains the raw data on the dry weight of the coarse roots, litter and stumps per subplot</li></ul>
IODP Expedition 391 Carbonates composite report
This composite report includes data from two analyses (total carbon from Elemental analysis [CHNS], and inorganic carbon from [Coulometer]). Each row combines the CHNS and Coulometer data from measurements made on the same sample at the same time for a particular section and section offset (depth). If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate data type (Elemental analysis and Coulometer). If the same sample was measured multiple times by any of the methods, results in the report will be combined on one line where possible. Each additional replicate result will be shown in subsequent rows and will be combined where possible. Report includes results for carbon forms: total, inorganic, calcium carbonate, and organic by difference, along with total hydrogen, nitrogen, and sulfur.
IODP Expedition 391 Inorganic carbon (coulometer)
Inorganic carbon (carbonate) is determined by coulometry, which uses a photodetection cell to measure carbon dioxide evolved during sample acidification. Report includes percent inorganic carbon and calcium carbonate.
IODP Expedition 397T Inorganic carbon (coulometer)
Inorganic carbon (carbonate) is determined by coulometry, which uses a photodetection cell to measure carbon dioxide evolved during sample acidification. Report includes percent inorganic carbon and calcium carbonate.
IODP Expedition 397T Carbonates composite report
This composite report includes data from two analyses (total carbon from Elemental analysis [CHNS], and inorganic carbon from [Coulometer]). Each row combines the CHNS and Coulometer data from measurements made on the same sample at the same time for a particular section and section offset (depth). If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate data type (Elemental analysis and Coulometer). If the same sample was measured multiple times by any of the methods, results in the report will be combined on one line where possible. Each additional replicate result will be shown in subsequent rows and will be combined where possible. Report includes results for carbon forms: total, inorganic, calcium carbonate, and organic by difference, along with total hydrogen, nitrogen, and sulfur.
IODP Expedition 383 Carbonates composite report
This composite report includes data from two analyses (total carbon from Elemental analysis [CHNS], and inorganic carbon from [Coulometer]). Each row combines the CHNS and Coulometer data from measurements made on the same sample at the same time for a particular section and section offset (depth). If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate data type (Elemental analysis and Coulometer). If the same sample was measured multiple times by any of the methods, results in the report will be combined on one line where possible. Each additional replicate result will be shown in subsequent rows and will be combined where possible. Report includes results for carbon forms: total, inorganic, calcium carbonate, and organic by difference, along with total hydrogen, nitrogen, and sulfur.
The potential of nitric acid-functionalized carbon nanotubes to mitigate bacterial biofilms
<p>Pristine multi-walled carbon nanotubes were functionalized with nitric acid, followed by thermal treatment at 600 °C, and incorporated into a poly(dimethylsiloxane) matrix. The composites were characterized and their antibiofilm activity and antibacterial mechanisms were assessed by biofilm cell culturability and flow cytometry, respectively.</p>
Analyzing marine biofilms developed on carbon nanotube-modified surfaces by 3D OCT approach
<p>Glass, epoxy resin, and carbon nanotubes (CNT) composite were analyzed regarding wettability by water contact angle measurement, and roughness by atomic force microscopy. Cyanobacterial biofilms formed by Nodosilinea cf. nodulosa LEGE 10377 were developed on these surfaces for seven weeks and under controlled hydrodynamic conditions. Biofilm wet weight and structural parameters such as biofilm thickness, contour coefficient, biovolume, porosity, and average size of non-connected pores obtained from Optical Coherence Tomography (OCT) were assessed.</p>
Dataset from paper "Quantifying landscape fragmentation and forest carbon dynamics over 35 years in the Brazilian Atlantic Forest"
<h3><strong><span>Dataset from the paper “Quantifying landscape fragmentation and forest carbon dynamics over 35 years in the Brazilian Atlantic Forest”</span></strong></h3> <p><span> </span><span>This repository contains:</span></p> <ul> <li><span>Dataset Description: “raster_labels.xlsx” (an Excel spreadsheet detailing raster pixel values and their respective fragmentation classes).</span></li> <li><span>Fragmentation Raster Files: “forest_fragmentation_mspa_2020.tif” and “forest_fragmentation_mspa_2020.tif” (GeoTIFF files of landscape forest fragmentation for 1985 and 2020).</span></li> </ul> <p><span> </span><span>If you need anything else, please contact the corresponding author, Igor Broggio (<a href="mailto:isbbroggio@gmail.com">isbbroggio@gmail.com</a>).</span></p> <p><span> </span></p> <p><span>If you use these data, please cite the paper: </span><span>[Citation]</span></p>
Tweets on carbon dioxide removal
<div> <h1><span>Growing online attention and positive sentiments towards</span><br><span>carbon dioxide removal</span></h1> <p>Tim Repke, Finn Müller-Hansen, Emily Cox, Jan Minx</p> <p><em><span>(unpublished)</span></em></p> <p><span>Scaling up CO2 removal is crucial to achieve net-zero targets and limit global warming. </span><span>Understanding public perception of large-scale carbon dioxide removal (CDR) is vital to </span><span>avoid opposition that could slow down development, investments, and deployment. <br></span><span>Using Twitter data from 2010 to 2022, we analysed attention and sentiments towards ten </span><span>CDR methods. Our study provides up-to-date time series evidence complementing survey </span><span>studies, capturing the opinions of users with knowledge or awareness of emerging CDR </span><span>methods. </span><span>Attention towards CDR has grown exponentially, particularly in recent years. <br></span><span>Overall, </span><span>the discourse on CDR has become more positive, except for BECCS. Conventional CDR </span><span>methods are the most discussed and receive more positive sentiments. We examined three </span><span>user types, each with varying levels of involvement in the discourse.</span> <span>Infrequent users (as</span><span>sumed less familiar) pay more attention to methods with biological sinks, while frequent </span><span>users (assumed more familiar) focus more on novel CDR methods.</span></p> <h3><span>Dataset description</span></h3> <p><strong><span>export.csv<br></span></strong><span>This dataset contains all Twitter IDs of tweets retrieved for this study. We also include all technology annotations, which technology-specific subquery this relates to, sentiment classification, and user type. Note, that this dataset contains more tweets than used in the study.</span></p> <p><strong>UserPanels.csv<br></strong>This is an overview of all users, their categorisation, and the number of positive/negative/neutral tweets. This could also be derived from the export.csv.</p> </div> <div> <div> </div> <div> </div> </div>
Carbon fluxes data over Indian spring wheat agro-ecosystem
<p>The data consists of the following:</p> <ol> <li>Site-scale carbon flux data for an IARI experimental wheat site for the growing season 2013–2014 in New Delhi (28°40' N, 77°12' E).</li> <li>The simulation data in NetCDF format comprises carbon fluxes such as GPP, NPP, Ra, Rh, and NEE.</li> <li>Harvested wheat area of spring wheat across the Indian wheat-growing regions.</li> <li>Site-scale NEP (gC/m2/mon) measured at Meerut (29°05′33″N, 77°41′53″E; growing season 2009-2010) and Saharanpur (29° 52′ 19.139″ N and 077° 34′ 01.621″ E; growing season 2014-15) extracted from published work (Patel et al., 2011; Patel et al., 2021, respectively)</li> </ol>
Integrated global assessment of the natural forest carbon potential (tifs)
<p>Since we have large data files for the maps used in the paper 'Integrated global assessment of the natural forest carbon potential', we have uploaded the maps separately here. After downloading the maps, you can place them in the path: Data/BiomassMergedMaps. Then, the code for making figures will be replicable.</p> <p>This is version 1.1, which includes the addition of the 'readMe.txt' and the soil carbon potential map, and corrections to each model's maps in TGB for both full and net potential.</p>
Regulation of Dye-decolorizing Peroxidases Gene Expression in Pleurotus ostreatus Grown on Glycerol as the Carbon Source
<p>This dataset contains the raw data and code necessary to reproduce the results of: Regulation of dye peroxidas gene expression in Pleurotus ostreatus grown on glycerol as the carbon source.</p> <p> </p> <p>These data are also available at github: <a href="https://github.com/JLuisCuamatzi/Pleurotus_ostreatus_CarbonSources">JLuisCuamatzi/Pleurotus_ostreatus_CarbonSources: Data and scripts to reproduce the analysis performed at Regulation of dye peroxidas gene expression in Pleurotus ostreatus grown on glycerol as the carbon source (github.com)</a></p>
Database to: Cover crops affect pool specific soil organic carbon in cropland – A meta‐analysis
<p>Database to a meta-analysis studying the effects of cover crops on the mineral-associated organic carbon pool (MAOC), the particulate organic carbon pool (POC) and the microbial biomass carbon pool (MBC). Consists of:<br>1. information on the database<br>2. legend<br>3. list of included studies, all extracted data necessary for response ratio calculation and moderator analysis, and additional information</p>
Qiime2 classifiers (rbcl, Mollusc 18s) for testing the validity of using eDNA for carbon origin analysis from sediment cores
<p>Qiime2 formatted classifiers that were created for a Natural England funded project by researchers at the James Hutton Institute. The pilot project aims to test the validity of using eDNA for carbon origin analysis from sediment cores. These classifiers for the rbcl and 18 Mollusc genes were made using RESCRIPt and Qiime2. </p> <p>The scripts used to created these classifiers are available at the James Hutton ICS GitHub <a href="https://github.com/HuttonICS/blue-carbon-db">blue-carbon-db</a> . The files are as follows:</p> <p><a href="../api/records/10046481/draft/files/mollusc-espineira-classifier.qza/content" target="_blank" rel="noopener noreferrer">mollusc-espineira-classifier.qza</a> is a classifer built from ncbi 18s Mollusc sequences, trained on the primer set from Espiñeira et al (2009).</p> <div>rbcl-vasselon-zimmerman-F3-R1-classifier.qza is a classifer built from ncbi rbcl sequences, trained on the F3 and R1 primer set fromVasselon et al (2017).</div> <p> </p> <p> </p> <p><strong>Important: </strong>If you use these classifiers please be aware of the process used to create them and be sure to review the methods. These databases were created by downloading data from the NCBI in October 2023, sequence data available at the NCBI changes over time. To create the most up to date database a fresh download and re-evaluations of the databases would be preferable. All method and scripts can be found at <a href="https://github.com/HuttonICS/blue-carbon-db">blue-carbon-db </a></p> <p>If you use these database please reference this repository along with RESCRIPt and Qiime2 </p> <p> </p> <p>Espiñeira, M., González-Lavín, N., Vieites, J. M. and Santaclara, F. J. 2009 Development of a method for the genetic identification of commercial bivalve species based on mitochondrial 18S rRNA sequences. J Agric Food Chem, 28, 495-502 https://doi.org/10.1021/jf802787d</p> <p> </p> <p>Vasselon, V., Rimet, F., Tapolczai, K. and Bouchez, A. 2017. Assessing ecological status with diatoms DNA metabarcoding: Scaling-up on a WFD monitoring network (Mayotte island, France). Ecological Indicators, 82, 1-12 <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ecolind.2017.06.024" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ecolind.2017.06.024</a></p>
Comparative electrochemical study of veterinary drug – danofloxacin – at glassy carbon electrode and electrified liquid-liquid interface
<p>Data set for the paper " Comparative electrochemical study of veterinary drug – danofloxacin – at glassy carbon electrode and electrified liquid-liquid interface"</p>
SEM atlas of selected carbon nanomaterials
<p>Atlas of SEM images of commercially available carbon nanomaterials. Magnifications: x2000 - x100000.</p>
A taxonomy to map evidence on the co-benefits, challenges, and limits of carbon dioxide removal
<p>This repository is linked to the following article:</p> <ul> <li>Prütz, R., Fuss, S., Lück, S. Stephan, L. & Rogelj, J., A taxonomy to map evidence on the co-benefits, challenges, and limits of carbon dioxide removal. <em>Commun Earth Environ</em> <strong>5</strong>, 197 (2024). <a href="https://doi.org/10.1038/s43247-024-01365-z">https://doi.org/10.1038/s43247-024-01365-z</a></li> </ul> <p>This repository includes: </p> <ul> <li>The literature-based data set that was compiled and used to develop the taxonomy of carbon dioxide removal side effects</li> <li>Code to run the machine learning classifier and to process and visualise the data</li> <li>Training data and an abbreviation list which is required to run the provided code</li> </ul>
IODP Expedition 378 Carbonates composite report
This composite report includes data from two analyses (total carbon from Elemental analysis [CHNS], and inorganic carbon from [Coulometer]). Each row combines the CHNS and Coulometer data from measurements made on the same sample at the same time for a particular section and section offset (depth). If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate data type (Elemental analysis and Coulometer). If the same sample was measured multiple times by any of the methods, results in the report will be combined on one line where possible. Each additional replicate result will be shown in subsequent rows and will be combined where possible. Report includes results for carbon forms: total, inorganic, calcium carbonate, and organic by difference, along with total hydrogen, nitrogen, and sulfur.
IODP Expedition 378 Inorganic carbon (coulometer)
Inorganic carbon (carbonate) is determined by coulometry, which uses a photodetection cell to measure carbon dioxide evolved during sample acidification. Report includes percent inorganic carbon and calcium carbonate.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.