Emissions data files by emission species (SO2, NOx, BC, OC, NH3, NMVOC, CO, CO2, CH4, N2O), country, sector, and fuel produced by the July-08-2024 release of CEDS.

See the CEDS GitHub site for details including journal paper reference information and any known issues with this data.

The three file bundles are:

CEDS_v_2024_07_08_aggregate.zip (emissions by sector, by country, by fuel, by country and fuel, by country and sector, and by sector and fuel)
CEDS_v_2024_07_08_detailed.zip (emissions by country, sector, and fuel)
CEDS_v_2024_07_08_supplementary_bunkers.zip (Additional detail for aviation and shipping by country)

Associated gridded data for this release will be available on ESGF shortly.(Metadata for this record is still under construction...)

Gridded data to be produced from the April release of the CEDS data system (CEDS v_2021_04_21). Data is in a format identical to the CMIP6 data on ESGF, but extends to 2019. This version is downscaled to 0.1 degrees largely using EDGAR emissions.

Emissions data files by emission species (SO2, NOx, BC, OC, NH3, NMVOC, CO, CO2, CH4), country, and sector produced by the Dec-23-2019 release of CEDS (http://doi.org/10.5281/zenodo.3592073).

See the CEDS GitHub site for details.

These represent incremental updates to the data described in Hoesly et al. (2018).

The Common Entity Data Standards (CEDS) Domain Entity Schema (DES) provides a hierarchy of domains, entities, categories, and elements. It is intended for use primarily by people as an index to search, map, and organize elements in a logical way. [from homepage]

{"references": ["Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q. (2018) Historical (1750\u20132014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369-408. doi: 10.5194/gmd-11-369-2018.", "Hoesly, R. P. O'Rourke, C. Braun, L. Feng, S. J. Smith, T. Pitkanen, J. J. Seibert, L. Vu, M. Presley, R. Bolt, B. Goldstein. (2019, December 23). JGCRI/CEDS: v-12-23-2019 (Version Dec-23-2019). Zenodo. http://doi.org/10.5281/zenodo.3592073"]} Emissions data files by emission species (SO2, NOx, BC, OC, NH3, NMVOC, CO, CO2, CH4, N2O), country, and sector produced by the Feb-05-2021 release of CEDS. See the CEDS GitHub site for details including journal paper reference information and known issues with this data.

CMIP6 Forcing Datasets (input4MIPs). These data include all datasets published for 'input4MIPs.CMIP6.CMIP.PNNL-JGCRI.CEDS-2017-08-30-supplemental-data' with the full Data Reference Syntax following the template 'activity_id.mip_era.target_mip.institution_id.source_id.realm.frequency.variable_id.grid_label'.

The model CEDS-2017-08-30-supplemental-data (CEDS-2017-08-30-supplemental-data) was run by the PNNL-JGCRI (PNNL-JGCRI) in native nominal resolutions: unknown.

Project: The forcing datasets (and boundary conditions) needed for CMIP6 experiments are being prepared by a number of different experts. Initially many of these datasets may only be available from those experts, but over time as part of the 'input4MIPs' activity most of them will be archived by PCMDI and served by the Earth System Grid Federation (https://esgf-node.llnl.gov/search/input4mips/ ). More information is available in the living document: http://goo.gl/r8up31 .

CMIP6 Forcing Datasets (input4MIPs). These data include all datasets published for 'input4MIPs.CMIP6.CMIP.PNNL-JGCRI.CEDS-2016-06-18-supplemental-data' with the full Data Reference Syntax following the template 'activity_id.mip_era.target_mip.institution_id.source_id.realm.frequency.variable_id.grid_label'.

The model CEDS-2016-06-18-supplemental-data (CEDS-2016-06-18-supplemental-data) was run by the PNNL-JGCRI (PNNL-JGCRI) in native nominal resolutions: unknown.

Project: The forcing datasets (and boundary conditions) needed for CMIP6 experiments are being prepared by a number of different experts. Initially many of these datasets may only be available from those experts, but over time as part of the 'input4MIPs' activity most of them will be archived by PCMDI and served by the Earth System Grid Federation (https://esgf-node.llnl.gov/search/input4mips/ ). More information is available in the living document: http://goo.gl/r8up31 .

CEDS v_2024_10_21 Release Gridded Emissions Data 0.5 degree

This Zenodo data entry is a documentation placeholder for the CEDS v_2024_10_21 0.5 degree gridded data released via ESGF.

*************

Errors were found in some of this data. Those files have been redacted from ESGF and replaced with corrected files labeled CEDS v_2024_11_25.

Air emissions for all species, NMVOC bulk emissions, and supplementary speciated VOCs from this version are still up to date and available on ESGF.

*************

This data is derived from CEDS v_2024_07_08 aggregate emissions release, which includes emissions data files by emission species (SO2, NOx, BC, OC, NH3, NMVOC, CO, CO2, CH4, N2O), country, and sector produced by the July-08-2024 release of CEDS and released here:
https://zenodo.org/records/12803197

This data set can be accessed via ESGF, for detailed instructions on how to access and download, as well as data notes, see the README file attached.

See the CEDS GitHub site for details including journal paper reference information and any known issues with this data:
https://github.com/JGCRI/CEDS

CMIP6 Forcing Datasets (input4MIPs). These data include all datasets published for 'input4MIPs.CMIP6.CMIP.PNNL-JGCRI.CEDS-2016-07-26-sectorDim' with the full Data Reference Syntax following the template 'activity_id.mip_era.target_mip.institution_id.source_id.realm.frequency.variable_id.grid_label'.

The model CEDS-2016-07-26-sectorDim (CEDS-2016-07-26-sectorDim) was run by the PNNL-JGCRI (PNNL-JGCRI) in native nominal resolutions: unknown.

Project: The forcing datasets (and boundary conditions) needed for CMIP6 experiments are being prepared by a number of different experts. Initially many of these datasets may only be available from those experts, but over time as part of the 'input4MIPs' activity most of them will be archived by PCMDI and served by the Earth System Grid Federation (https://esgf-node.llnl.gov/search/input4mips/ ). More information is available in the living document: http://goo.gl/r8up31 . This data version 2016-07-26-sectorDim is deprecated. Please use the current version(s) 2017-05-18,2017-08-30,2017-10-05; see http://goo.gl/r8up31 for more information

Release of gridded greenhouse gas emissions from 2000-2019 based on the 2021_04_21 CEDS release with direct inclusion of point sources as time series. This dataset contains just the primary emissions species covered by CEDS, both at 0.5° and 0.1° spatial resolution. Data for speciated VOC emissions can be found in the companion dataset, DOI 10.5281/zenodo.7526534.

*Version 2 soon to be released, fixing an error of some missing point sources.*

Data in these digital opportunity dashboards comes from students' and families' answers to the Digital Opportunity Data Collection, which school districts use to gather data on home internet and learning device access for students in their districts. While this is an optional data collection, DPI encouraged districts to collect this information and push it to WISEdata to help drive statewide initiatives to improve digital learning opportunity in Wisconsin. Data is given in percentages to protect student privacy. View statewide digital opportunity data on the WISEdash Public Portal.The digital opportunity questions are the result of a coordinated effort with the Council of Chief State School Officers (CCSSO), Education SuperHighway, and the Ed-Fi Alliance (affiliated with the Dell Foundation). In May 2021, the US Department of Education added these questions as data elements to the Common Educational Data Standard (CEDS). CEDS is the federal government’s framework for all education data, adding significant validation to the questions and items. See the questions DPI provided to districts to use in their surveys here.

Recommended citation

Gütschow, J.; Busch, D.; Pflüger, M. (2024): The PRIMAP-hist national historical emissions time series v2.6.1 (1750-2023). zenodo. doi:10.5281/zenodo.15016289.

Gütschow, J.; Jeffery, L.; Gieseke, R.; Gebel, R.; Stevens, D.; Krapp, M.; Rocha, M. (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, doi:10.5194/essd-8-571-2016

Content

• Use of the dataset and full description
• Abstract
• Support
• Sources
• Files included in the dataset
• Notes
• Data format description (columns)
• References
• Changelog

Abstract

The PRIMAP-hist dataset combines several published datasets to create a comprehensive set of greenhouse gas emission pathways for every country and Kyoto gas, covering the years 1750 to 2023, and almost all UNFCCC (United Nations Framework Convention on Climate Change) member states as well as most non-UNFCCC territories. The data resolves the main IPCC (Intergovernmental Panel on Climate Change) 2006 categories. For CO2, CH4, and N2O subsector data for Energy, Industrial Processes and Product Use (IPPU), and Agriculture are available. The "country reported data priority" (CR) scenario of the PRIMAP-hist datset prioritizes data that individual countries report to the UNFCCC.

For developed countries, AnnexI in terms of the UNFCCC, this is the data submitted anually in the "National Inventory Submissions". Until 2023 data was submitted in the "Common Reporting Format" (CRF). Since 2024 the new "Common Reporting Tables" (CRT) are used. For developing countries, non-AnnexI in terms of the UNFCCC, we use the "Biannial Transparency Reports" (BTR) which mostly come with data also using the "Common Reporting Tables". We also use older data available through the UNFCCC DI portal (di.unfccc.int) and additional country submissions from "Biannial Update Reports" (BUR), "National Communications" (NC), and "National Inventory Reports" (NIR) read from pdf and where available xls(x) or csv files. For a list of these submissions please see below. For South Korea the 2023 official GHG inventory has not yet been submitted to the UNFCCC but is included in PRIMAP-hist. PRIMAP-hist also includes official data for Taiwan which is not recognized as a party to the UNFCCC. We have mostly replaced the official data that has not been submitted to the UNFCCC used in v2.6 as countries have now submitted their data in CRT format, but had to make some exceptions as the CRT data was not usable for all countries.

Gaps in the country reported data are filled using third party data such as CDIAC, EI (fossil CO2), Andrew cement emissions data (cement), FAOSTAT (agriculture), and EDGAR 2024 (all sectors for CO2, CH4, N2O, HFCs, PFCs, SF6, NF3, except energy CO2). Lower priority data are harmonized to higher priority data in the gap-filling process.

For the third party priority time series gaps in the third party data are filled from country reported data sources.

Data for earlier years which are not available in the above mentioned sources are sourced from EDGAR-HYDE, CEDS, and RCP (N2O only) historical emissions.

The v2.4 release of PRIMAP-hist reduced the time-lag from 2 to 1 years for the October release. Thus the present version 2.6.1 includes data for 2023. For energy CO2 growth rates from the EI Statistical Review of World Energy are used to extend the country reported (CR) or CDIAC (TP) data to 2023. For CO2 from cement production Andrew cement data are used. For other gases and sectors we use EDGAR 2024 data. In a few cases we have to rely on numerical methods to estimate emissions for 2023.

Version 2.6.1 of the PRIMAP-hist dataset does not include emissions from Land Use, Land-Use Change, and Forestry (LULUCF) in the main file. LULUCF data are included in the file with increased number of significant digits and have to be used with care as they are constructed from different sources using different methodologies and are not harmonized.

The PRIMAP-hist v2.6.1 dataset is an updated version of

Gütschow, J.; Pflüger, M.; Busch, D. (2024): The PRIMAP-hist national historical emissions time series v2.6 (1750-2023). zenodo. doi:10.5281/zenodo.13752654.

The Changelog indicates the most important changes. You can also check the issue tracker on github.com/JGuetschow/PRIMAP-hist for additional information on issues found after the release of the dataset. Detailed per country information is available from the detailed changelog which is available on the primap.org website and on zenodo.

Use of the dataset and full description

Before using the dataset, please read this document and the article describing the methodology, especially the section on uncertainties and the section on limitations of the method and use of the dataset.

Gütschow, J.; Jeffery, L.; Gieseke, R.; Gebel, R.; Stevens, D.; Krapp, M.; Rocha, M. (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, doi:10.5194/essd-8-571-2016

Please notify us (johannes.guetschow@climate-resource.com) if you use the dataset so that we can keep track of how it is used and take that into consideration when updating and improving the dataset.

When using this dataset or one of its updates, please cite the DOI of the precise version of the dataset used and also the data description article which this dataset is supplement to (see above). Please consider also citing the relevant original sources when using the PRIMAP-hist dataset. See the full citations in the References section further below.

Since version 2.3 we use the data formats developed for the PRIMAP2 climate policy analysis suite: PRIMAP2 on GitHub. The data are published both in the interchange format which consists of a csv file with the data and a yaml file with additional metadata and the native NetCDF based format. For a detailed description of the data format we refer to the PRIMAP2 documentation.

We have also included files with more than three significant digits. These files are mainly aimed at people doing policy analysis using the country reported data scenario (HISTCR). Using the high precision data they can avoid questions on discrepancies with the reported data. The uncertainties of emissions data do not justify the additional significant digits and they might give a false sense of accuracy, so please use this version of the dataset with extra care.

Support

If you encounter possible errors or other things that should be noted, please check our issue tracker at github.com/JGuetschow/PRIMAP-hist and report your findings there. Please use the tag "v2.6.1" in any issue you create regarding this dataset.

If you need support in using the dataset or have any other questions regarding the dataset, please contact johannes.guetschow@climate-resource.com.

Climate Resource makes this data available CC BY 4.0 licence. Free support is limited to simple questions and non-commercial users. We also provide additional data, and data support services to clients wanting more frequent updates, additional metadata or to integrate these datasets into their workflows. Get in touch at contact@climate-resource.com if you are interested.

Sources

• Global CO2 emissions from cement production v250226 data, paper: Andrew
  (2025), Andrew (2019)
• EI Statistical Review of World Energy website: Energy Institute (2024)
• CDIAC data: Hefner and Marland (2023), data: Hefner (2024), paper: Gilfillan and Marland (2021)
• CEDS: data: Hoesly et al. (2020), paper: Hoesly et al. (2018)
• EDGAR 2024: data/website: European Commission, European Commision, JRC (2024), report: European Commission. Joint Research Centre & IEA. (2024)
• EDGAR-HYDE 1.4 data: Van Aardenne et al. (2001), Olivier and Berdowski (2001)
• FAOSTAT database data: Food and Agriculture Organization of the United Nations (2024)
• RCP historical data data, paper: Meinshausen et al. (2011)
• UNFCCC National Communications and National Inventory Reports for developing countries available from the UNFCCC DI portal <a

This dataset focuses on a sample of 105 Italian cities that have declared a climate emergency by the end of February 2021. It provides key data and information on the selected cities, the contents of their Climate Emergency Declarations (CEDs) and Local Climate Plans (LCPs), both mitigation and adaptation.

It is organised into four spreadsheets containing the following data respectively: 1. General key data on the city sample: List of cities, Province, Region, Latitude, Longitude, Population, Classes of population, Surface area, Adhesion to: C40 / Climate Allliance / Covenant of Mayors / Green City Network 2. Cities by macroregions / regions / provinces and by population classes
3. Climate Emergency Declarations (CEDs) of the sample cities (as of 28 February 2021). It includes the List of cities, CED date, Supporting documents/websites, and outcomes of the content analysis of CEDs, in terms of: references to national petitions, to the Friday for Future movement, to CEDAMIA, to the IPCC Report 2018, and to the Sustainable Development Goals, CO2/GHG targets, links/adhesions to transnational climate networks, references to LCP and their targets, mentions to Adaptation, Local air pollution, and support citizens' initiatives in favour of the climate, requests to local institutions (Regions) and to the government to take climate. 4. Local Climate Plans (LCPs) of the sample cities (as of 19 April 2021). It includes information on the availability of SEAP/SECAP within the Covenant of Mayors, Web source, Name of the MITIGATION plan, Approval date, and the outcomes of the content analysis of LCPs, in terms of: CO2/CO2eq emission target, baseline year, target year, carbon neutrality target and target year, web source, mentions to Local air pollution, adaptation plans (integrated or stand-alone), web source.

CMIP6 Forcing Datasets (input4MIPs). These data include all datasets published for 'input4MIPs.CMIP6.CMIP.PNNL-JGCRI.CEDS-2016-06-18' with the full Data Reference Syntax following the template 'activity_id.mip_era.target_mip.institution_id.source_id.realm.frequency.variable_id.grid_label'.

The model CEDS-2016-06-18 (CEDS-2016-06-18) was run by the PNNL-JGCRI (PNNL-JGCRI) in native nominal resolutions: unknown.

Project: The forcing datasets (and boundary conditions) needed for CMIP6 experiments are being prepared by a number of different experts. Initially many of these datasets may only be available from those experts, but over time as part of the 'input4MIPs' activity most of them will be archived by PCMDI and served by the Earth System Grid Federation (https://esgf-node.llnl.gov/search/input4mips/ ). More information is available in the living document: http://goo.gl/r8up31 . This data version 2016-06-18 is deprecated. Please use the current version(s) 2017-05-18,2017-08-30,2017-10-05; see http://goo.gl/r8up31 for more information

Data Summary: EQUATES: EPA’s Air QUAlity TimE Series Project The US EPA developed a set of modeled meteorology, emissions, air quality and pollutant deposition spanning the years 2002 through 2019. Modeled datasets cover the Conterminous US (CONUS) at a 12km horizontal grid spacing (12US1) and the Northern Hemisphere at a 108km (108NHEMI) using WRFv4.1.1 for meteorology and CMAQv5.3.2 for air quality modeling. New hemispheric and North American emissions inventories were developed using, to the extent possible, consistent input data and methods across all years, including emissions from mobile, fire, and oil and gas sources. Collectively these model outputs represent 100s of TB of data. We have selected a subset of the model input and output datasets that we hope will be most useful to the air quality research community. These datasets include: 2002-2017 monthly and annual emissions totals for 9 pollutants: NOX, SO2, CO, PM2.5, primary organic carbon (POC), primary elemental carbon (PEC), VOC, non-methane organic gases (NMOG), NH3 Emissions inventory files for the CONUS for 2002-2019 suitable for input into the Sparse Matrix Operator Kernel Emissions (SMOKE) emission processor CMAQ-ready emissions, initial conditions and boundary condition input files for the 12US1 domain for 2013-2019 CMAQ-ready meteorology files for the 12US1 domain for 2002-2019. Matched surface meteorology model output with surface observations for 2002-2019 Daily average CMAQ estimated concentration for 14 pollutants for the 12US1 domain for 2002-2019 Annual total CMAQ estimated deposition (wet and dry) for the 12US1 domain for 2002-2019 Daily average 3D CMAQ output for 44 layers for the 108NHEMI domain for 2009–2019 Note: The 2002-2017 emissions summary files are included as part of this Dataverse repository as zipped comma separated ASCII files. (Note, 2018 and 2019 emission summary data are not included but are available upon request.) This repository also includes two zip files with the CMAQ source code used for running CMAQ on the 12US1 and 108NHEMI domains. The remaining modeling datasets are on either the Google Drive or the AWS Open Data Program. The metadata associated with this DOI contain the link to the Google Drive folder and instructions for downloading the modeling data. File Location and Download Instructions on Google Drive: Link to EQUATES Data Dictionary and Data Use Statement Link to EQUATES emissions, meteorology, and air quality data Link to sample scripts for downloading EQUATES datasets Link to EQUATES tutorial and sample run scripts for running CMAQ with EQUATES input data Publication on EQUATES emissions: Foley et al. (2023) Please direct questions about the EQUATES datasets to the CMAS User Forum EQUATES category. File Location and Download Instructions on AWS Open Data Program: EQUATES Data on Open Data Program EQUATES Data Dictionary Instructions to download data from AWS Open Data Program Simulation Settings and Inputs: Meteorology Inputs for 108NHEMI and 12US1 CMAQ Simulations Model: Weather Research Forecast model, version 4.1.1 (WRF v4.1.1) Land Cover: 500m MODIS Sea surface temperature data (12US1 only): NAM SST Wind data (12US1 only): VAD Data assimilation analysis fields for 108NHEM: GFS 1 degree data for 2002-2019 Data assimilation analysis fields for 12US1: 40km AWIP for 2002-2005; 12km NAM for 2006-2019 with ERA data used when NAM data was missing WRF v4.1.1 options: Morrison Microphysics; RRTMG longwave and shortwave radiation; Pleim Surface Layer; Pleim-Xiu Land-Surface model; ACM2 Boundary layer mixing; Kain-Fritsch + Ma and Tan (2009) trigger 2 (KF2) for sub-grid convection scheme; 3-D grid nudging (GRID_FDDA) and indirect soil nudging (pxlsm_soil_nudge); no lightning assimilation WRF post-processing: Meteorology-Chemistry Input Processor (MCIP) v5.0. Emissions Inputs for 108NHEMI CMAQ Simulation US Anthropogenic emissions: EQUATES 12km emissions gridded for the 108 km domain Non-US Anthropogenic emissions: 2010 HTAP with country/sector/year scaling factors based on CEDS data used to create emissions for 2002-2009 and 2011-2014. 2015-2017 emissions created using CEDS scaling factors for 2014 (i.e., emissions trends are flat for 2014-2017). Emissions for 2018 and 2019 were developed at a later date and are based on 2010 HTAP with country/sector/year scaling factors based on CEDS version 2021 04 21 . Emissions supplemented with Canada emissions from Environment and Climate Change Canada and China emissions from Zhao et al. (2018) Lightning NO: GEIA based monthly climatology using vertical profiles applied by season and latitude Fire emissions: SMARTFIRE2 and BlueSky Pipeline (U.S.) and FINNv1.5 (non-U.S.) Biogenic VOC: Hourly CAMSv2.1 data (Sindelarova et al.; extension of Megan2.1) for 2002-2019 based on monthly mean values with diurnal scaling factors Soil NO: Hourly CAMSv2.1 data (CAMS_D81.3.8.2; extension of Yienger and Levy (1995)) for 2002-2019 based on monthly...

The purpose of the study was to investigate how and why injuries occur to police and citizens during use of force events. The research team conducted a national survey (Part 1) of a stratified random sample of United States law enforcement agencies regarding the deployment of, policies for, and training with less lethal technologies. Finalized surveys were mailed in July 2006 to 950 law enforcement agencies, and a total of 518 law enforcement agencies provided information on less lethal force generally and on their deployment and policies regarding conducted energy devices (CEDs) in particular. A total of 292 variables are included in the National Use of Force Survey Data (Part 1) including items about weapons deployment, force policies, training, force reporting/review, force incidents and outcomes, and conducted energy devices (CEDs). Researchers also collected agency-supplied use of force data from law enforcement agencies in Richland County, South Carolina; Miami-Dade, Florida; and Seattle, Washington; to identify individual and situational predictors of injuries to officers and citizens during use of force events. The Richland County, South Carolina Data (Part 2) include 441 use-of-force reports from January 2005 through July 2006. Part 2 contains 17 variables including whether the officer or suspect was injured, 8 measures of officer force, 3 measures of suspect resistance, the number of witnesses and officers present at each incident, and the number of suspects that resisted or assaulted officers for each incident. The Miami-Dade County, Florida Data (Part 3) consist of 762 use-of-force incidents that occurred between January 2002 and May 2006. Part 3 contains 15 variables, including 4 measures of officer force, the most serious resistance on the part of the suspect, whether the officer or suspect was injured, whether the suspect was impaired by drugs or alcohol, the officer's length of service in years, and several demographic variables pertaining to the suspect and officer. The Seattle, Washington Data (Part 4) consist of 676 use-of-force incidents that occurred between December 1, 2005, as 15 variables, including 3 measures of officer force, whether the suspect or officer was injured, whether the suspect was impaired by drugs or alcohol, whether the suspect used, or threatened to use, physical force against the officer(s), and several demographic variables relating to the suspect and officer(s). The researchers obtained use of force survey data from several large departments representing different types of law enforcement agencies (municipal, county, sheriff's department) in different states. The research team combined use of force data from multiple agencies into a single dataset. This Multiagency Use of Force Data (Part 5) includes 24,928 use-of-force incidents obtained from 12 law enforcement agencies from 1998 through 2007. Part 5 consists a total of 21 variables, including the year the incident took place, demographic variables relating to the suspect, the type of force used by the officer, whether the suspect or officer was injured, and 5 measures of the department's policy regarding the use of CEDs and pepper spray. Lastly, longitudinal data were also collected for the Orlando, Florida and Austin, Texas police departments. The Orlando, Florida Longitudinal Data (Part 6) comprise 4,222 use-of-force incidents aggregated to 108 months -- a 9 year period from 1998 through 2006. Finally, the Austin, Texas Longitudinal Data (Part 7) include 6,596 force incidents aggregated over 60 months- a 5 year period from 2002 through 2006. Part 6 and Part 7 are comprised of seven variables documenting whether a Taser was implemented, the number of suspects and officers injured in a month, the number of force incidents per month, and the number of CEDs uses per month.

Provide the spatial distribution of the annual emissions of BC, CH4, CO2, CO, NH3, NMVOC, NOx, OC and SO2 from agriculture, energy exploitation, industrial and fuel combustion, surface transportation, residential and commercial housing, solvent production, waste disposal and international shipping in China from 1990 to 2015, in kg/m2/yr. The spatial precision is 0.5 °, and the geographic coordinate system is WGS84. The data comes from the CEDs data set. The historical homogenized land use data of China is obtained by linear time interpolation, Chinese regional mask extraction and coordinate system transformation of the original data, and saved in geotiff file format. The methods and standards of data over the years are consistent, the coverage is complete, and the collection and processing process is traceable and reliable.

Data in this digital opportunity map comes from students' and families' answers to the Internet Access at Home Survey, which school districts use to gather data on home internet and learning device access for students in their districts. While this is an optional data collection, DPI encouraged districts to collect this information and push it to WISEdata to help drive statewide initiatives to improve digital learning opportunity in Wisconsin. Data is given in percentages to protect student privacy. View statewide digital opportunity data on the WISEdash Public Portal.The digital opportunity questions are the result of a coordinated effort with the Council of Chief State School Officers (CCSSO), Education SuperHighway, and the Ed-Fi Alliance (affiliated with the Dell Foundation). In May 2021, the US Department of Education added these questions as data elements to the Common Educational Data Standard (CEDS). CEDS is the federal government’s framework for all education data, adding significant validation to the questions and items. See the questions DPI provided to districts to use in their surveys here.