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13 results for “anthropogenic carbon”
Simulations for: The anthropogenic imprint on temperate and boreal forest demography and carbon turnover
<p>LPJ-GUESS model output underlying analysis in:<br> Thomas A. M. Pugh, Rupert Seidl, Daijun Liu, Mats Lindeskog, Louise P. Chini, Cornelius Senf, The anthropogenic imprint on temperate and boreal forest demography and carbon turnover, Global Ecology and Biogeography. 10.1111/geb.13773</p> <p>For a full description of the simulations, please refer to the above paper. If using the data please cite this dataset and the publication above.</p> <p>Files are provided as netcdf4 files. Basic metadata is included in the headers of the individual files.</p> <p># Simulation types<br> _standard_nat_2014 -> Best estimate simulation under natural disturbance. Averaging period 2001-2014<br> _high_nat_2014 -> Upper estimate simulation under natural disturbance. Averaging period 2001-2014<br> _low_nat_2014 -> Lower estimate simulation under natural disturbance. Averaging period 2001-2014<br> _standard_nat_1990 -> Best estimate simulation under natural disturbance. Averaging period 1961-1990<br> _standard_natcc_2014 -> Best estimate simulation based on closed-canopy forest area calculations under natural disturbance. Averaging period 2001-2014<br> _standard_anthro_2014 -> Best estimate simulation under natural and anthropogenic disturbance. Averaging period 2001-2014<br> _high_anthro_2014 -> Upper estimate simulation under natural and anthropogenic disturbance. Averaging period 2001-2014<br> _low_anthro_2014 -> Lower estimate simulation under natural and anthropogenic disturbance. Averaging period 2001-2014<br> _site_recovery_Eurasia_nodist -> Site simulations for 4 Eurasian sites looking at the successional sequence. 800 years long under constant spinup environmental conditions.<br> _site_recovery_America_nodist -> Site simulations for 5 North American sites looking at the successional sequence. 800 years long under constant spinup environmental conditions.</p> <p># Variables (for units see netcdf metadata)<br> Cveg -> Live vegetation carbon<br> Clitter -> Litter carbon<br> Csoil -> Soil carbon<br> LAI -> Leaf area index<br> NPP -> Net primary productivity<br> GPP -> Gross primary productivity<br> distprob -> Natural disturbance probability<br> age -> Stand age structure<br> temprange -> Annual temperature range (based on monthly means)<br> wooddensity -> community mean wood density</p> <p>Note:<br> All nat simulations assume that forest covers the whole grid cell.<br> All anthro simulations assume that forest only covers the primary and secondary fractions of the grid cell, as defined in the LUH2 dataset, however values are given relative to the whole grid cell. I.e. value_on_forest_area * (primary_area_fraction+secondary_area_fraction).</p>
Global health burden of ambient PM2.5 and the role of anthropogenic black carbon and organic aerosols
<p><strong>SI Dataset S1 (</strong><strong>SI DataS1)</strong></p> <p>Excess mortality from ambient PM<sub>2<em>.</em>5 </sub>exposure among adults, children, and neonates.</p> <p><strong>SI Dataset S2 (</strong><strong>SI DataS2)</strong></p> <p>Pie charts showing distribution of excess death by disease among adults, children, and neonates.</p> <p><strong>SI Dataset S3 (</strong><strong>SI DataS3)</strong></p> <p>Sector contribution to ambient PM<sub>2<em>.</em>5</sub>-related excess death under EqT and 2BSP assumptions</p> <p><strong>SI Dataset S4 (</strong><strong>SI DataS4)</strong></p> <p>Excess death from ambient BC exposure and contributions of major anthropogenic sectors.</p> <p><strong>SI Dataset S5 (</strong><strong>SI DataS5)</strong></p> <p>Excess death from ambient POA exposure and contribution of major anthropogenic sectors.</p> <p><strong>SI Dataset S6 (</strong><strong>SI DataS6)</strong></p> <p>Excess death from ambient aSOA exposure and contribution of major anthropogenic sectors.</p> <p><strong>SI Dataset S7 (</strong><strong>SI DataS7)</strong></p> <p>Sector contribution to excess death under EqT and 2BSP relative toxicity assumptions by major regions.</p>
Historical (1979 - 2020) data for anthropogenic inputs to a catchment and riverine mainstem exports for carbon, nitrogen, and phosphorus
<p>We estimated the difference in Net Anthropogenic Nitrogen and Phosphorus Inputs (NANI-NAPI) at the finest scale possible (the municipality) in the <em>Rivière du Nord</em> watershed (Québec, Canada) between 1981 and 2016. The dataset here reports the delta between those two years for each municipality in the watershed.</p> <p>Three sites along the mainstem of <em>Rivière du Nord </em>have been sampled ~bi-monthly from ~1979 - 2020 for dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP), from which we estimated annual riverine export at each site. We also include annual precipitation (as the sum of rain and snow), and NANI-NAPI interpolated for each sub-watershed for 1981, 1986, 1991, 1996, 2001, 2006, 2011, and 2016.</p> <p> </p> <p> </p>
Dataset associated with the manuscript "A comprehensive assessment of anthropogenic and natural sources and sinks of Australasia's carbon budget" by Villalobos et al. (2023), part of the the second phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2).
<p>Dataset associated with the manuscript "A comprehensive assessment of anthropogenic and natural sources and sinks of Australasia’s carbon budget" by Villalobos et al. (2023), part of the the second phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2). </p>
Data set for the study "Assessing the lifetime of anthropogenic CO2 and its sensitivity to different carbon cycle processes"
<p>This repository contains the data necessary to reproduce the results of the paper: <br>"Assessing the lifetime of anthropogenic CO<sub>2</sub> and its sensitivity to different carbon cycle processes" <br><a href="https://doi.org/10.5194/bg-22-2767-2025" target="_blank" rel="noopener">https://doi.org/10.5194/bg-22-2767-2025</a></p> <h3><strong>Data organization:</strong></h3> <p>The Zenodo upload is organized as the following inside of <code>results.zip</code>:</p> <ul> <li>Data analysis and figure generation are given by "*.pynb" and "*.m" files<br><br></li> <li>Data files as NetCDF output are organized with the following structure inside of <code>data</code>:<br><br> <ul> <li><strong>Experiment</strong>: <code>REF</code>, <code>noLAND</code>, <code>noWEATH</code>, <code>ECS2</code>, <code>ECS4</code>, <code>intCH4</code>, <code>PATH1</code>, <code>PATH2</code>, and <code>PULSE</code><br><br> <ul> <li><strong>Emissions scenario</strong>: <code>0_gtc</code>, <code>500_gtc</code>, <code>1000_gtc</code>, <code>2000_gtc</code>, <code>3000_gtc</code>, <code>4000_gtc</code>, and <code>5000_gtc</code><br><br> <ul> <li><strong>Component</strong>: atmosphere (<code>atm</code>), land (<code>lnd</code>), ocean (<code>ocn</code>), biogeochemistry (<code>bgc</code>), and the carbon cycle (<code>co2</code>)<br> <ul> <li>Note: for <code>intCH4</code>, there is another file concerning methane (<code>ch4</code>)</li> <li>Note: surface ocean pH and surface ocean DIC were not part of the standard output in the original CLIMBER-X model. Instead, these variables were calculated during post-processing using 2D spatial data. Since the 2D data was only output every 1 kyr, the first millennium of data was missing. To address this, we re-ran the experiments with surface ocean pH and DIC included in the output for the first 1 kyr. This is why there are additional individual files for pH, DIC, and the Revelle factor (see "fig5_7_8_9.ipynb" for further details).<br><br></li> </ul> </li> <li><strong>File type</strong>: for each component, files are divided into timeseries (<code>*_ts.nc</code>) or 2D data with a 1 kyr output frequency (<code>*.nc</code>)<br> <ul> <li>Note: due to size constraints of the Zenodo repository, only some 2D spatial data presented in the publication (for the <code>REF</code> experiment) is available. However, this is not an exhaustive dataset. For inquiries regarding additional data, please contact the corresponding author to explore potential availability.</li> </ul> </li> </ul> </li> </ul> </li> </ul> </li> </ul>
Combined data file for Jilbert et al. "Anthropogenic Inputs of Terrestrial Organic Matter Influence Carbon Loading and Methanogenesis in Coastal Baltic Sea Sediments", Frontiers in Earth Science 9, 2021
<p>The datafile contains all the new raw data presented in the figures in the publication.</p>
Data used in manuscript Spatial modelling of local-scale biogenic and anthropogenic carbon dioxide emissions in Helsinki
<p>This data set includes data used to develop and evaluate carbon dioxide emission modelling component in the Surface Urban Energy and Water balance Scheme (SUEWS). The data files are:</p> <ol> <li>CO2_Model_Parameter_Fitting.zip contains m-files (Matlab) used to calculate parameters for photosynthesis modelling <ul> <li>F_pho_data.mat includes meteorological and EC data used to fit photosynthesis model parameters in Kumpula</li> <li>FitKumpulaData.m calculates the model parameters in Kumpula</li> <li>FitViikkiData.m calculates the model parameters in Viikki</li> <li>Other m-files needed by the above two codes</li> </ul> </li> <li>Data.zip contains measured data used to develop and evaluate SUEWS <ul> <li>KumpulaData2012.txt and TorniData2012.txt include eddy covariance data measured at the two sites in Helsinki</li> <li>SMEARIII_meteorology_2016MM_30.m meteorological data used to fit model parameters in Viikki street trees (see 00 ReadMe_SMEARIII_Meteorology.TXT for details)</li> <li>Viikki_SWC_2016.txt measured soil moisture from Viikki in 2016</li> <li>Kumpula_2016_HH_RLAI6_Output.out is SPP output used to fit model parameters in Viikki street trees</li> </ul> </li> <li>SUEWS_EC_Site_Model_runs: SUEWS input and output files for Kumpula and Torni model runs</li> <li>SpatialRun_input.zip: SUEWS input files for the spatial model run</li> <li>spatmatHel_final.mat: SUEWS output files for spatial model run in mat-format</li> </ol>
Anthropogenic carbon monoxide emissions during 2014-2020 in China constrained by in-situ observations
<p><strong>The description of the NetCDF files (12×200×350):</strong></p> <ol> <li> <p>The first dimension represents the months, the second represents latitude, and the third represents longitude.</p> </li> <li> <p>The latitude ranges from 15.1°N to 54.9°N, and the longitude ranges from 66.1°E to 135.9°E, with a uniform grid spacing of 0.2° for both.</p> </li> </ol> <p><strong>The units for all files are as follows:</strong></p> <table style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 33.2913%;"><col style="width: 33.2913%;"><col style="width: 33.2913%;"></colgroup> <tbody> <tr> <td> <p>File</p> </td> <td> <p>Format</p> </td> <td> <p>Unit</p> </td> </tr> <tr> <td> <p>All emission data.zip</p> </td> <td> <p>netcdf</p> </td> <td> <p>kg·m<sup>-2</sup>·s<sup>-1</sup></p> </td> </tr> <tr> <td> <p>Emissions in seven regions.csv</p> </td> <td> <p>csv</p> </td> <td> <p>10<sup>3</sup> kt</p> </td> </tr> <tr> <td> <p>Simulated CO concentrations.zip</p> </td> <td> <p>txt</p> </td> <td> <p>μg·m<sup>-3</sup> </p> </td> </tr> </tbody> </table>
Impacts of anthropogenic emission change scenarios on U.S. water and carbon balances at national and state scales in a changing climate
Open the record for dataset details and reuse information.
Ocean Heat Content Reconstructions based on Anthropogenic Carbon
<p>Data from "<strong>Heat and carbon coupling reveals ocean warming due to circulation changes</strong>" by Bronselaer & Zanna, 2020, Nature, https://doi.org/10.1038/s41586-020-2573-5</p> <p>The files contain Linear Change in Ocean Heat Content (top 2000 m) relative to 1951 for observations and CMIP5 data, and the decomposition into added and redistributed (due to changes in ocean circulation). </p>
LENS and NoPin (NP) ensemble means for apparent oxygen utilization (AOU), anthropogenic and preindustrial carbon, pCFC-12, and ideal age from Olivarez et al. (2023)
<p>Manuscript title: <strong>"How does the Pinatubo eruption influence our understanding of long-term changes in ocean biogeochemistry?"</strong></p> <p>Authors: Holly C. Olivarez<sup>1,2</sup>, Nicole S. Lovenduski<sup>2,3</sup>, Yassir A. Eddebbar<sup>4</sup>, Amanda R. Fay<sup>5</sup>, Galen A. McKinley<sup>5</sup>, Michael N. Levy<sup>6</sup>, and Matthew C. Long<sup>6</sup></p> <p>Affiliations:<br> <sup>1</sup>Department of Environmental Studies, University of Colorado, Boulder, CO, USA <br> <sup>2</sup>Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, USA<br> <sup>3</sup>Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, USA <br> <sup>4</sup>Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA <br> <sup>5</sup>Columbia University and Lamont-Doherty Earth Observatory, Palisades, NY, USA <br> <sup>6</sup>Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA</p> <p>LENS and No Pinatubo (NoPin in manuscript, NP in file names) CESM ensemble means for apparent oxygen utilization (AOU), anthropogenic and preindustrial carbon, <em>p</em>CFC-12, and ideal age along GO-SHIP transects akin to <a href="https://cchdo.ucsd.edu/data/4925/33RO20130803do.pdf">A16N</a>, <a href="https://cchdo.ucsd.edu/data/9276/33RO20131223do.pdf">A16S</a>, <a href="https://cchdo.ucsd.edu/data/14283/33RO20150525_do.pdf">P16N</a>, <a href="https://cchdo.ucsd.edu/cruise/320620140320#note_334284">P16S</a>, <a href="https://cchdo.ucsd.edu/cruise/09AR20060102">SO4I</a>, <a href="https://cchdo.ucsd.edu/cruise/320620180309">SO4P</a>.</p> <p>The CESM source code is freely available at <a href="http://www2.cesm.ucar.edu">http://www2.cesm.ucar.edu</a>. The model outputs described in this paper can be accessed at <a href="http://www.earthsystemgrid.org">www.earthsystemgrid.org</a>.</p>
Anthropogenic Carbon Emission System, 2012-2017, Version 2
This dataset provides estimates of hourly carbon dioxide (CO2) emissions from the combustion of fossil fuels at 1-km resolution for the coterminous United States (CONUS) covering the years 2012 through 2017. Emissions from the ACES model are reported for ten distinct emissions source sectors: Airports and Aircraft, Commercial Buildings, Electric Power Generation facilities, Industrial point and non-point sources, Commercial Marine Vessels, Nonroad vehicles and equipment, Oil and Gas wells and facilities, Onroad vehicles, Railway engines and yards, and Residential buildings. All emissions are reported hourly on a 1-km x 1-km spatial grid. The data are provided in NetCDF version 4 format.
Carbon Cycling to Climatic and Anthropogenic Perturbations in Tampa Bay and Biscayne Bay
Measurements made under the Response of Carbon Cycling to Climatic and Anthropogenic Perturbations in Two North American Subtropical Estuaries, near Tampa Bay and Biscayne Bay. Collaboration with USF, Upenn, and FIU.
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