We are provoding a set of table and maps that provides summary of ecosystem carbon balance (pools and fluxes) as simulated by the Dynamic Organic Soil version of the Terrestrial Ecosystem Model. Simulations are provided for the historical period from 1950 to 2009 and projections from 2010 to 2099, for the four main landscape conservation cooperative regions in Alaska (i.e. the Arctic, the Western Alaska, the North Pacific and the Northwest Boreal LCCs). Projections have been conducted at 1km-resolution for two set of climate scenarios for the A1B, B1 and A2 emission scenarios of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES). The two global circulation models used for these projections are (1) the 5th generation of the ECHAM general circulation model from the Max Planck Institute for Meteorology (ECHAM5), and (2) the fourth generation global circulation model from the Canadian Centre for Climate Modelling and Analysis (CCCMA). Pools and fluxes are summarized for uplands and lowlands separately. Vegetation carbon pools only concern living biomass. Soil carbon pools include organic layers, 1m deep mineral layers and dead woody debris. Positive fluxes indicate carbon assimilated to the ecosystem. Negative fluxes indicate carbon released to the atmosphere. Carbon fluxes are vegetation Net Primary Productivity (NPP), soil Heterotrophic respiration (HR), CO & CO2 and CH4 fire emissions from organic layer and vegetation burning (PYRO_COCO2 and PYRO_CH4 respectively), biogenic CH4 fluxes (BIO_CH4) and Net Ecosystem Carbon Balance (NECB).

Data Description Managed turfgrass is a common component of urban landscapes that is expanding under current land use trends. Previous studies have reported high rates of soil carbon sequestration in turfgrass, but no systematic review has summarized these rates nor evaluated how they change as turfgrass ages. We conducted a meta-analysis of soil carbon sequestration rates from 63 studies. Those data, as well as the code used to analyze them and create figures, are shared here. Dataset Development We conducted a systematic review from Nov 2020 to Jan 2021 using Google Scholar, Web of Science, and the Michigan Turfgrass Information File Database. The search terms targeted were "soil carbon", "carbon sequestration", "carbon storage", or “carbon stock”, with "turf", "turfgrass", "lawn", "urban ecosystem", or "residential", “Fescue”, “Zoysia”, “Poa”, “Cynodon”, “Bouteloua”, “Lolium”, or “Agrostis”. We included only peer-reviewed studies written in English that measured SOC change over one year or longer, and where grass was managed as turf (mowed or clipped regularly). We included studies that sampled to any soil depth, and included several methodologies: small-plot research conducted over a few years (22 datasets from 4 articles), chronosequences of golf courses or residential lawns (39 datasets from 16 articles), and one study that was a variation on a chronosequence method and compiled long-term soil test data provided by golf courses of various ages (3 datasets from Qian & Follett, 2002). In total, 63 datasets from 21 articles met the search criteria. We excluded 1) duplicate reports of the same data, 2) small plot studies that did not report baseline SOC stocks, and 3) pure modeling studies. We included five papers that only measured changes in SOC concentrations, but not areal stocks (i.e., SOC in Mg ha-1). For these papers, we converted from concentrations to stocks using several approaches. For two papers (Law & Patton, 2017; Y. Qian & Follett, 2002) we used estimated bulk densities provided by the authors. For the chronosequences reported in Selhorst & Lal (2011), we used the average bulk density reported by the author. For the 13 choronosequences reported in Selhorst & Lal (2013), we estimated bulk density from the average relationship between percent C and bulk density reported by Selhorst (2011). For Wang et al. (2014), we used bulk density values from official soil survey descriptions. Data provenance In most cases we contacted authors of the studies to obtain the original data. If authors did not reply after two inquiries, or no longer had access to the data, we captured data from published figures using WebPlotDigitizer (Rohatgi, 2021). For three manuscripts the data was already available, or partially available, in public data repositories. Data provenance information is provided in the document "Dataset summaries and citations.docx". Recommended Uses We recommend the following to data users:

Consult and cite the original manuscripts for each dataset, which often provide additional information about turfgrass management, experimental methods, and environmental context. Original citations are provided in the document "Dataset summaries and citations.docx". For datasets that were previously published in public repositories, consult and cite the original datasets, which may provide additional data on turfgrass management practices, soil nitrogen, and natural reference sites. Links to repositories are in the document "Dataset summaries and citations.docx". Consider contacting the dataset authors to notify them of your plans to use the data, and to offer co-authorship as appropriate.

This page provides data for the Carbon Neutrality performance measure.The City of Tempe is committed to protecting the environment. Carbon emissions are a significant contributor to the pollution of our atmosphere. Sources of carbon emissions include the energy used in city buildings and facilities, and in the fuel used in transit, city vehicles, and employee commuting. This performance measure puts the City on a path to being a carbon neutral city. The municipal carbon footprint includes buildings, streetlights, water treatment electricity, and fuel usage for fleet, transit, solid waste and employee commute.The performance measure dashboard is available at 4.19 Carbon Neutrality.Additional InformationSource: City pisions: fleet, WUD, solid waste. APS, SRP, MAG, SHROG and Valley MetroContact: Grace KellyContact E-Mail: Grace_Kelly@tempe.govData Source Type: CSVPreparation Method: It is part of a larger data set and uses proprietary software.Publish Frequency: Every 5 yearsPublish Method: ManualData Dictionary

Global carbon dioxide emissions from fossil fuels and industry totaled 37.01 billion metric tons (GtCO₂) in 2023. Emissions are projected to have risen 1.08 percent in 2024 to reach a record high of 37.41 GtCO₂. Since 1990, global CO₂ emissions have increased by more than 60 percent. Who are the biggest emitters? The biggest contributor to global GHG emissions is China, followed by the United States. China wasn't always the world's biggest emitter, but rapid economic growth and industrialization in recent decades have seen emissions there soar. Since 1990, CO₂ emissions in China have increased by almost 450 percent. By comparison, U.S. CO₂ emissions have fallen by 6.1 percent. Nevertheless, the North American country remains the biggest carbon polluter in history. Global events cause emissions to drop The outbreak of COVID-19 caused global CO₂ emissions to plummet some 5.5 percent in 2020 as a result of lockdowns and other restrictions. However, this wasn't the only time in recent history when a major global event caused emissions reductions. For example, the global recession resulted in CO₂ levels to fall by almost two percent in 2009, while the recession in the early 1980s also had a notable impact on emissions. On a percentage basis, the largest annual reduction was at the end of the Second World War in 1945, when emissions decreased by 17 percent.

These datasets represent a revised national scale estimate of wetland soil carbon stock assessments by improving representation of soil organic carbon densities. This assessment is based on a three-step approach to harmonize survey and point-based data for predicting soil organic carbon density from percent organic carbon alone (or percent organic matter, with conversion), when reliable dry bulk density information is not available. Given issues with survey-level extrapolation of soil pedons into discontinuous hydric soils, quantile, segmented data analysis provides a more accurate spatially explicit soil organic carbon density product. These modeled data leverage spatial and statistical distributions of soil organic carbon percent data of the conterminous United States (CONUS) for two national-scale soil datasets: a wetland-specific field campaign, the EPA National Wetland Condition Assessment, and the USDA NRCS SSURGO survey. See https://doi.org/10.3389/fsoil.2021.706701 for det ...

The burning of fossil fuels releases carbon dioxide into the atmosphere. CO2 is a greenhouse gas, and is primarily responsible for human-induced climate change. The trend: upward—sharply—especially among emerging nations such as China, India, and Brazil.Colors represent total CO2 emissions by year between 1960 and 2007.Red circles differentiate the top ten and top 50 emitters of CO2 in 2007. Click on the circles to see graphs of emissions over time.Click the play button on the time slider at the bottom of the page to see emission rates between 1960 and 2007.Data courtesy of the World Bank.

As a commitment to sustainability, our city joined the Global Covenant of Mayors for Climate and Energy. Tempe is setting a path to sustainability and resilience with our first ever Climate Action Plan (CAP). This CAP serves as a guideline for the City of Tempe’s path toward a sustainable and resilient future that will benefit the entire city. It is a detailed framework for measuring and reducing GHG emissions and climate change impacts. The CAP includes an inventory of previous years’ GHG emissions, Tempe’s emissions reduction goals, and prioritized actions. This dataset provides the community Greenhouse Gas emissions for the City of Tempe. Community greenhouse gas emissions inventories are a way for cities to track community greenhouse gas emissions. Currently, cities consume over two thirds of the world's energy and account for more than 70% of global CO2 emissions. (ICLEI) Tempe conducted a greenhouse gas inventory based on 2015 calendar year data to measure the community's greenhouse gas emissions.City staff worked with a consultant who recommended re-evaluating baseline data, from 2015. 2015 data has been updated accordingly.This page provides data for the Community Carbon Neutrality performance measure. The performance measure dashboard is available at 4.18 Community Carbon Neutrality.Additional InformationSource: Various sources including municipal resources, APS, SRP, SW Gas, and Maricopa Association of Governments.Contact (author): Grace Kelly Contact E-Mail (author): Grace_Kelly@tempe.govContact (maintainer): Braden KayContact E-Mail (maintainer): Braden_Kay@tempe.govData Source Type: TablePreparation Method: Transportation, fuel and energy use data are collected from various sources for residential, commercial and industrial uses in the community and estimates of the amount of emissions are calculated using the ICLEI's ClearPath tool.Publish Frequency: Every 5 yearsPublish Method: ManualData Dictionary

Jan 2, 2018 -- Mangrove soil carbon database updated to include reported and calculated bulk density and OC values. Model outputs were updated on Dec 20, 2017. This project used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Specifically this dataset contains: 1) a compilation of georeferenced and harmonized soil profile data under mangroves compiled from literature, reports and unpublished contributions 2) global mosaics of soil carbon stocks to 1m and 2m depths produced at 100 m resolution 3) tiled predictions of soil carbon stocks produced at 30 m resolution 4) shape file containing the tiling system 5) shape file containing country boundaries used for calculating national level statistics 30m data can be quickly visualized at: https://storage.googleapis.com/gfiske1/global_mangrove/index_w_slider.html

EU Carbon Permits rose to 72.06 EUR on July 3, 2025, up 0.18% from the previous day. Over the past month, EU Carbon Permits's price has fallen 0.76%, but it is still 2.68% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for EU Carbon Permits.

GRACEnet (Greenhouse gas Reduction through Agricultural Carbon Enhancement network) is a research program initiated in the early 2000s . Goals are to better quantify greenhouse gas GHG emissions from cropped and grazed soils under current management practices and to identify and further develop improved management practices that will enhance carbon (C) sequestration in soils, decrease GHG emissions, promote sustainability and provide a sound scientific basis for carbon credits and GHG trading programs. This program generates information that is needed by agro-ecosystem modelers, producers, program managers and policy makers. Coordinated multi-location field studies follow standardized protocols to compare net GHG emissions (carbon dioxide, nitrous oxide, methane), C sequestration, crop/forge yields, and broad environmental benefits under different management systems that: Typify existing production practices Maximize C sequestration Minimize net GHG emissions Meet sustainable production and broad environmental benefit goals (including C sequestration, net GHG emissions, water, air and soil quality, etc.) Resources in this dataset:Resource Title: GRACEnet Brochure 2016. File Name: GRACENET brochure REVISED June 2017.pdfResource Title: Data Entry Template 2017. File Name: DET_GRACEnet_REAP.zipResource Description: Includes Excel templates for Experiment description worksheets, Site characterization worksheets, Management worksheets, Measurement worksheets where experimental unit data are reported, and Information that may be useful to the user, including drop down lists of treatment specific information and ranges of expected values. General and introductory instructions, as well as a Data Validation check are also included.Resource Title: GRACEnet Brochure 2017. File Name: GRACENET brochure REVISED July 2017 final.pdfResource Title: GRACEnet-NUOnet Data Dictionary. File Name: GRACEnet-NUOnet_DD.csvResource Title: GRACEnet Data Search. File Name: natres.zipResource Description: The attached file contains data from all sites as of February 9, 2022. For an interactive and up to date version of data visit https://usdaars.maps.arcgis.com/apps/MapSeries/index.html?appid=b66de747da394ed5aeab07dc9f50e516

These are data from soil CO2 flux surveys done in the Utah FORGE study area near Roosevelt Hot Springs. Concentration is in units of ppm and is the final concentration of CO2 in the chamber after the up-to-2-minute flux measurement. Flux is in units of grams of CO2 per m^2.

The Carbon Storage Open Database is a collection of spatial data obtained from publicly available sources published by several NATCARB Partnerships and other organizations. The carbon storage open database was collected from open-source data on ArcREST servers and websites in 2018, 2019, 2021, and 2022. The original database was published on the former GeoCube, which is now EDX Spatial, in July 2020, and has since been updated with additional data resources from the Energy Data eXchange (EDX) and external public data resources. The shapefile geodatabase is available in total, and has also been split up into multiple databases based on the maps produced for EDX spatial. These are topical map categories that describe the type of data, and sometimes the region for which the data relates. The data is separated in case there is only a specific area or data type that is of interest for download. In addition to the geodatabases, this submission contains: 1. A ReadMe file describing the processing steps completed to collect and curate the data. 2. A data catalog of all feature layers within the database. Additional published resources are available that describe the work done to produce the geodatabase: Morkner, P., Bauer, J., Creason, C., Sabbatino, M., Wingo, P., Greenburg, R., Walker, S., Yeates, D., Rose, K. 2022. Distilling Data to Drive Carbon Storage Insights. Computers & Geosciences. https://doi.org/10.1016/j.cageo.2021.104945 Morkner, P., Bauer, J., Shay, J., Sabbatino, M., and Rose, K. An Updated Carbon Storage Open Database - Geospatial Data Aggregation to Support Scaling -Up Carbon Capture and Storage. United States: N. p., 2022. Web. https://www.osti.gov/biblio/1890730 Morkner, P., Rose, K., Bauer, J., Rowan, C., Barkhurst, A., Baker, D.V., Sabbatino, M., Bean, A., Creason, C.G., Wingo, P., and Greenburg, R. Tools for Data Collection, Curation, and Discovery to Support Carbon Sequestration Insights. United States: N. p., 2020. Web. https://www.osti.gov/biblio/1777195 Disclaimer: This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

This data set provides a soil map with estimates of soil carbon (C) in g C/m2 for 20-cm layers from the surface to one meter depth for the conterminous United States.STATSGO v.1 (State Soil Geographic Database, Soil Survey Staff, 1994) data were used to estimate by 20-cm intervals to a 1-m depth the mean soil carbon for each of the STATSGO-delineated soil map units. These map units are the polygons represented in the provided Shapefile data product.

The dataset provides the statistics on Greenhouse Gas Emissions and Carbon Intensity in Hong Kong.

This offer includes high-precision, carbon emission-focused LCA datasets covering Materials, Production (Processes and Machines), and Energy, enabling companies to conduct accurate Product Carbon Footprint (PCF) calculations. The data is region-specific, updated bi-annually, and aligned with ISO 14067 and GHG Protocol standards. Customers can access the datasets via API, CSV files, or the sustamize Data Platform, ensuring seamless integration into LCA tools, PLM systems, and sustainability reporting workflows. By utilizing these comprehensive CO₂ datasets, businesses can enhance supply chain transparency, improve Scope 3 emissions tracking, and ensure compliance with global sustainability regulations. Please refer to: https://docs.sustamizer.com/knowledge-hub/database-overview/overview for more info.

Data presented are on carbon (C) and nitrogen (N) inputs, and changes in soil C and N in eight systems during the first eight years of a tillage-intensive organic vegetable systems study that was focused on romaine lettuce and broccoli production in Salinas Valley on the central coast region of California. The eight systems differed in organic matter inputs from cover crops and urban yard-waste compost. The cover crops included cereal rye, a legume-rye mixture, and a mustard mixture planted at two seeding rates (standard rate 1x versus high rate 3x). There were three legume-rye 3x systems that differed in compost inputs (0 versus 7.6 Mg ha−1 vegetable crop−1) and cover cropping frequency (every winter versus every fourth winter). The data include: (1) changes in soil total organic C and total N concentrations and stocks and nitrate N (NO3-N) concentrations over 8 years, (2) cumulative above ground and estimated below ground C and N inputs, cover crop and crop N uptake, and harvested crop N export over 8 years, (3) soil permanganate oxidizable carbon (POX-C) concentrations and stocks at time 0, 6 and 8 years, and (4) cumulative, estimated yields of lettuce and broccoli (using total biomass and harvest index values) over the 8 years. The C inputs from the vegetables and cover crops included estimates of below ground inputs based on shoot biomass and literature values for shoot:root. The data in this article support and augment information presented in the PLoS ONE research article “Winter cover crops increase readily decomposable soil carbon, but compost drives total soil carbon during eight years of intensive, organic vegetable production in California”. Resources in this dataset:Resource Title: Supplementary materials. File Name: Web Page, url: https://ars.els-cdn.com/content/image/1-s2.0-S2352340920313639-mmc1.zip Zipped Excel (xlsx) data comprising Supplementary Table 1: Raw data of soil total organic carbon concentrations, total nitrogen concentrations, nitrate nitrogen concentrations, total organic carbon stocks, and total nitrogen stocks over 8 years from the Salinas Organic Cropping Systems experiment in Salinas, California. This includes data from all eight systems in the experiment. The related article in PLoS ONE only included data from five of the eight systems with optimal seeding rates for weed suppression. Supplementary Table 2: Raw data of cumulative cover crop and vegetable carbon inputs, legume nitrogen fixation, cover crop and vegetable crop N uptake and export during 8 years at the Salinas Organic Cropping Systems experiment in Salinas, California. This includes data from all eight systems in the experiment. The related article in PLoS ONE only included data from five of the eight systems with optimal seeding rates for weed suppression. Supplementary Table 3: Raw data of soil permanganate oxidizable carbon (POX-C) concentrations and stocks at the 0 to 6.7 cm depth in years 0 and 6, and the 0 to 30 cm depth in year 8 from the Salinas Organic Cropping Systems experiment in Salinas, California This data from five of the eight systems with optimal seeding rates for weed suppression was included the related paper in PLoS ONE. Supplementary Table 4: Raw data of cumulative, estimated yields of lettuce and broccoli crop during 8 years at the Salinas Organic Cropping Systems experiment in Salinas, California; yields are on an oven-dry basis. This includes data from all eight systems in the experiment.

The NBCD 2000 (National Biomass and Carbon Dataset for the Year 2000) data set provides a high-resolution (30 m) map of year-2000 baseline estimates of basal area-weighted canopy height, aboveground live dry biomass, and standing carbon stock for the conterminous United States. This data set distributes, for each of 66 map zones, a set of six raster files in GeoTIFF format. There is a detailed README companion file for each map zone. There is also an ArcGIS shapefile (mapping_zone_shapefile.shp) with the boundaries of all the map zones. A mosaic image of biomass at 240 m resolution for the whole conterminous U.S. is also included.

Please read this important note regarding the differences of Version 2 from Version 1 of the NBCD 2000 data.

With Version 1, in some mapping zones, certain land cover types (in particular Shrubs, NLCD Type 52) were missing from and unaccounted for in modeled estimates because of a lack of reference data.

In Version 1, when landcover types were missing in the models, the model for the deciduous tree cover type was applied. While more woody vegetation was mapped, the authors think this had little effect on model performance as in most cases NLCD version 1 cover type was not a strong predictor of modeled estimates (See companion Mapping Zone Readme files).

In Version 2, after renewed modeling efforts and user feedback, these previously unaccounted for cover types are now included in modeled estimates.

All 66 mapping zones were updated with the previously unmapped land cover types now mapped. The authors recommend use of the new version for all analyses and will only support the updated version.

Development of the data set used an empirical modeling approach that combined USDA Forest Service Forest Inventory and Analysis (FIA) data with high-resolution InSAR data acquired from the 2000 Shuttle Radar Topography Mission (SRTM) and optical remote sensing data acquired from the Landsat ETM+ sensor. Three-season Landsat ETM+ data were systematically compiled by the Multi-Resolution Land Characteristics Consortium (MRLC) between 1999 and 2002 for the entire U.S. and were the foundation for development of both the USGS National Land Cover Dataset 2001 (NLCD 2001) and the Landscape Fire and Resource Management Planning Tools Project (LANDFIRE). Products from both the NLCD 2001 (landcover and canopy density) and LANDFIRE (existing vegetation type) projects as well as topographic information from the USGS National Elevation Dataset (NED) were used within the NBCD 2000 project as spatial predictor layers for canopy height and biomass estimation. Forest survey data provided by the USDA Forest Service FIA program were made available to the project under a national Memorandum of Understanding. The response variables (canopy height and biomass) used in model development and validation were derived from the FIA database (FIADB). Production of the NLCD 2001 and LANDFIRE projects was based on a mapping zone approach in which the conterminous U.S. was split into 66 ecoregionally distinct mapping zones. This mapping zone approach was also adopted by the NBCD 2000 project.

Cyprus Industry: Carbon Pricing Score: Including Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data was reported at 27.007 % in 2021. Cyprus Industry: Carbon Pricing Score: Including Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data is updated yearly, averaging 27.007 % from Dec 2021 (Median) to 2021, with 1 observations. The data reached an all-time high of 27.007 % in 2021 and a record low of 27.007 % in 2021. Cyprus Industry: Carbon Pricing Score: Including Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Cyprus – Table CY.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: Non OECD Member: Annual. The carbon pricing score answers the question how close countries are to price carbon in line with carbon costs. EUR 60 is a midpoint estimate for carbon costs in 2020, and a low-end estimate for 2030. Pricing all emissions at least at EUR 60 in 2020 shows that a country is on a good track to reach the goals of the Paris Agreement to decarbonise by mid-century economically. EUR 30 is a historic low-end estimate for carbon costs, and EUR 120 is a midrange estimate for carbon costs in 2030.; The carbon pricing score answers the question how close countries price carbon emissions in line with carbon costs. EUR 120 per tonne CO2 is a central estimate for carbon costs in 2030.More generally, a carbon pricing score of 100% shows that a country prices all carbon emissions at the carbon cost estimate or more, and a carbon pricing score of 0% shows that a country does not price any carbon emissions.The carbon pricing score by country, by sector answers the question how close countries price carbon emissions in line with carbon costs within a given sector.For additional information, see Effective Carbon Rates 2021

This dataset, “AquaMatch Dissolved Organic Carbon Data from Water Quality Portal ~1970-2024”, is a component of a forthcoming update to AquaSat (Ross et al., 2019), AquaSat version 2 (“V2”). The overarching purpose of AquaSat V2 is to emphasize the individual parts of the AquaSat pipeline that make-up the matchups between satellite and in-situ measurements. As such, we have greatly expanded and improved upon the AquaSat dissolved organic carbon dataset in two ways: First, we have incorporated additional recent in situ data beyond what was available at the publication of AquaSat. Second, we have created a data quality tiering system to provide end-users with more guidance on data usage. In this schema we have three tiers: restrictive data that are verifiably self-similar across organizations and time-periods and can be considered highly reliable; narrowed data that we have good reason to believe are self-similar, but for which we cannot verify full compatibility across data providers; and inclusive data, which are assumed to be reliable and are harmonized to our best ability given the information available from the data provider. We have also added flag columns to help users understand complexities of the available depth and field sampling data. This dataset is a derived data product created using records downloaded from the Water Quality Portal (WQP) spanning January 5, 1970, to June 27, 2024. The WQP is a data warehouse for water-related data measured or observed within the United States and US territories managed by the Environmental Protection Agency, United States Geological Survey, and the National Water Quality Monitoring Council. The dataset does not contain remote sensing matchups but can be paired with Landsat surface reflectances using the pipeline presented in Ross et al. (2019). Ross, M. R. V., Topp, S. N., Appling, A. P., Yang, X., Kuhn, C., Butman, D. et al. (2019). AquaSat: A data set to enable remote sensing of water quality for inland waters. Water Resources Research, 55, 10012–10025. https://doi.org/10.1029/2019WR024883

United States Road: Carbon Pricing Score: Including Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data was reported at 37.016 % in 2018. United States Road: Carbon Pricing Score: Including Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data is updated yearly, averaging 37.016 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 37.016 % in 2018 and a record low of 37.016 % in 2018. United States Road: Carbon Pricing Score: Including Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The carbon pricing score answers the question how close countries are to price carbon in line with carbon costs. EUR 60 is a midpoint estimate for carbon costs in 2020, and a low-end estimate for 2030. Pricing all emissions at least at EUR 60 in 2020 shows that a country is on a good track to reach the goals of the Paris Agreement to decarbonise by mid-century economically. EUR 30 is a historic low-end estimate for carbon costs, and EUR 120 is a midrange estimate for carbon costs in 2030.; The carbon pricing score answers the question how close countries price carbon emissions in line with carbon costs. EUR 120 per tonne CO2 is a central estimate for carbon costs in 2030.More generally, a carbon pricing score of 100% shows that a country prices all carbon emissions at the carbon cost estimate or more, and a carbon pricing score of 0% shows that a country does not price any carbon emissions.The carbon pricing score by country, by sector answers the question how close countries price carbon emissions in line with carbon costs within a given sector.For additional information, see Effective Carbon Rates 2021