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15 results for “carbon offsets”
Dataset of Norwegian forest albedo carbon offset potential
<p>This dataset contains the following six files in geotiff format with additional user detail provided as a README.txt file: 1) Forest albedo effect in C-equivalent units for the present day climate 2) Forest albedo effect in C-equivalent units for the transient 21st century RCP4.5 climate 3) Forest albedo's carbon offset potential for the present day climate 4) Forest albedo's carbon offset potential for the transient 21st century RCP4.5 climate 5) Site Index (productivity class) of dominant tree species 6) Dominant tree species 7) README</p> <p>The dataset contains results and input data related the following publication: <br>Bright, R. M., Cataneo, N., Antón-Fernández, C., Eisner, S., Astrup, R., "Relevance of surface albedo to forestry policy in high latitude and altitude regions may be overvalued". <em>Environmental Research Letters, <span><a href="https://doi.org/10.1088/1748-9326/ad657e">https://doi.org/10.1088/1748-9326/ad657e</a></span></em> </p>
Organic and inorganic data for soil cores from Brazil and Florida Bay seagrasses to support Howard et al 2018, CO2 released by carbonate sediment production in some coastal areas may offset the benefits of seagrass “Blue Carbon” storage, Limnology and Oceanography, DOI: 10.1002/lno.10621
Using piston corers, soils from Florida Bay and Brazilian seagrass meadows were collected to complete organic and inorganic carbon inventories for the top 1 m of soil. Instrumental analyses and loss on ignition at 500C were used to measure C content of downcore slices.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Tree Growth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes cumulative stem biomass carbon data (from pre-treatment in 2012 until 2022) and annual stem biomass growth rates (not cumulative) for 2015-2022 for the red maple trees at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Soil Temperature, Soil Frost, and Snow Depth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes soil temperature (winter 2021-2022) and snow depth and frost depth (winter 2022-2023) at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Yield increases mediated by pollination and carbon payments can offset restoration costs in coffee landscapes
<p>This dataset and code can be used to reproduce results from the article with the same title</p> <p>The scripts to generate the farm-level scenarios and the regional-level scenarios are as following:</p> <ul> <li><strong>farm-level</strong> = <em>optimization_scenarios.R</em></li> <li><strong>regional-level</strong> = <em>optimization_scenarios_rl.R</em></li> </ul> <p>The <strong>properties boundaries</strong> and <strong>APP limits</strong> for the municipalities considered in this study can be obtained from the adress:</p> <ul> <li><a href="https://www.car.gov.br/publico/imoveis/index">https://www.car.gov.br/publico/imoveis/index</a>.</li> </ul> <p>The <strong>list of municipalities</strong> is located at the file "list_mun.csv" within the tables folder.</p> <p>The raster with <strong>land-use and land-cover classes</strong> is classified as follows:</p> <ul> <li>class 0: all other uses;</li> <li>class 1: natural vegetation;</li> <li>class 2: coffee;</li> </ul> <p>The <strong>estimated yield per property</strong> is at the yield_estimation.csv file. Each property (n=507) is identified with an unique ID. The dataframe contains:</p> <ul> <li>the predicted yield in coffee bags/ha (<em>predictec_coffee_bags</em>);</li> <li>yield in USD/ha (<em>yield_USD_future</em>); the difference in yield bewteen the future scenarios and the baseline scenario (<em>diff_USD</em>);</li> <li>the net present value of the difference between the future scenarios and the baseline (<em>npv_yield_USD_future</em>)</li> </ul> <p>The script "merging_scen_land_use.R" was used to combine the restoration scenarios generated by the optimization model with the baseline land-use and land-cover;</p> <p> </p> <p> </p>
California's forest carbon offset buffer pool is severely undercapitalized
<p>A copy of the input, intermediate, and final output data files underlying the analysis and figures of Badgley et al., "California’s forest carbon offset buffer pool is severely undercapitalized."</p>
A global database of nature-based carbon offset project boundaries
<p><strong>Overview</strong></p> <p>Nature-based climate solutions (NBS) have become an important component of strategies aiming to reduce atmospheric CO2 and mitigate climate change impacts. Carbon offsets have emerged as one of the most widely implemented NBS strategies, however, these projects have also been criticized for exaggerating offsets. Verifying the efficacy of NBS-derived carbon offset is complicated by a lack of readily available geospatial boundary data. Herein, we detail methods and present a database of nature-based offset project boundaries. This database provides the locations of 575 NBS projects distributed across 55 countries. Geospatial boundaries were aggregated using a combination of scraping data from carbon project registries (<em>n</em>=433, 75.3%) as well as manual georeferencing and digitization (<em>n</em>=127, 22.1%). Database entries include three varieties of carbon projects: avoided deforestation, afforestation, reforestation and re-vegetation, and improved forest management. An accuracy assessment of the georeferencing and digitizing process indicated a high degree of accuracy (intersection over union score of 0.98 +/- 0.015).</p> <p>Details about using the database are provided in the README.txt file.</p>
Simplified boundaries of forest projects participating in California's forest carbon offset program
<p>A simplified version of active (including previously active) and listed forest carbon offset projects operating under California's forest carbon offset program. See archive's README for additional details.</p>
Using remote sensing to quantify the additional climate benefits of California forest carbon offset projects
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LULC input and CLM5 carbon output "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benefits."
<p>Land use land cover (LULC) files for the CESM and UKESM simulations performed for the study "Chemistry-albedo feedbacks from reforestation reduce climate benefits and crop yields. The input data was processed to make it compatible for UKESM as described in Weber et al (2022) https://doi.org/10.5194/egusphere-2022-748.</p>
Soil, litter and vegetation carbon for the 6 simulations performed in CLM5 of "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benef"
<p>Soil, litter and vegetation carbon for the 6 simulations performed in CLM5 (Table S1) of "Chemistry-albedo feedbacks from reforestation reduce climate benefits and crop yields"</p> <p>i.clm5.global_MF_SSP1.h1.2015-2100_zip.nc - SSP126_MF_Land</p> <p>i.clm5.global_SSP1_nolulcc.clm2.h1.2015-2100_zip.nc - SSP126_2015_Land </p> <p>i.clm5.global_SSP1.h1.2015-2100_zip.nc - SSP126_Land</p> <p>i.clm5.global_MF_SSP3.02.h1.2015-2100_zip.nc - SSP370_MF_Land</p> <p>i.clm5.global_SSP3.02.h1.2015-2100_zip.nc - SSP370_Land</p> <p>i.clm5.global_SSP3_nolulcc.clm2.h1.2015-2100_zip.nc - SSP370_2015_Land</p> <p> </p> <p>These simulations were performed by Dr James King, University of Sheffield.</p> <p> </p>
Photovoltaic Windows to Offset the Intensive Energy and Carbon Footprints of Highly Glazed Buildings
<p>Data generated by extensive building energy simulations to determine the impact of next-generation glazing technologies.</p>
Systematic over-crediting in California's forest carbon offsets program
<p>A repository containing the input, intermediate, and final output data files underlying the analysis and figures in Badgley et al., “Systematic over-crediting in California’s forest carbon offsets program”.</p>
Methane emissions in seagrass meadows as a small offset to carbon sequestration
<p>Station P: Masterfile includes environmental data and CO2, CH4 and radon concentration at Station P </p> <p>Station S: Masterfile includes the environmental data and CO2, CH4 and radon concentration at Station S </p> <p>Sediment Core: Master file includes the porewater DIC and CH4 concentration</p> <p>Survey: Master file of spatial survey includes GPS location, CH4 concentration </p>
Data from: Methane emission offsets carbon dioxide uptake in a small productive lake
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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)
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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.