7 datasets found
  1. Data from: Low-Income Energy Affordability Data - LEAD Tool - 2022 Update

    • catalog.data.gov
    • data.openei.org
    Updated Jan 22, 2025
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    U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (2025). Low-Income Energy Affordability Data - LEAD Tool - 2022 Update [Dataset]. https://catalog.data.gov/dataset/low-income-energy-affordability-data-lead-tool-2022-update
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    Dataset updated
    Jan 22, 2025
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Description

    The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

  2. Low-income Energy Affordability Data

    • redivis.com
    application/jsonl +7
    Updated Jul 25, 2023
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    Carnegie Mellon University Libraries (2023). Low-income Energy Affordability Data [Dataset]. https://redivis.com/datasets/82z6-1fgs5gkva
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    avro, arrow, parquet, application/jsonl, spss, stata, sas, csvAvailable download formats
    Dataset updated
    Jul 25, 2023
    Dataset provided by
    Redivis Inc.
    Authors
    Carnegie Mellon University Libraries
    Description

    Abstract

    Census tract level data of the Low-Income Energy Affordability Data (LEAD) Tool created by Office of Energy Efficiency and Renewable Energy, U.S. Department of Energy. Curated by Carnegie Mellon University Libraries.

    Methodology

    https://lead.openei.org/docs/LEAD-Tool-Methodology.pdf

    Usage

    License: Creative Commons Attribution

  3. d

    Low-Income Energy Affordability Data (LEAD) Tool.

    • datadiscoverystudio.org
    • data.amerigeoss.org
    • +1more
    csv, pdf, xlsb, xlsm +1
    Updated Jun 9, 2018
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    (2018). Low-Income Energy Affordability Data (LEAD) Tool. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/c8f6d43865e54a2cba876b4b433b1494/html
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    csv, pdf, xlsb, xlsm, xlsxAvailable download formats
    Dataset updated
    Jun 9, 2018
    Description

    description: ABOUT THIS TOOL: The Better Building s Clean Energy for Low Income Communities Accelerator (CELICA) was launched in 2016 to help state and local partners across the nation meet their goals for increasing uptake of energy efficiency and renewable energy technologies in low and moderate income communities. As a part of the Accelerator, DOE created this Low-Income Energy Affordability Data (LEAD) Tool to assist partners with understanding their LMI community characteristics. This can be utilized for low income and moderate income energy policy and program planning, as it provides interactive state, county and city level worksheets with graphs and data including number of households at different income levels and numbers of homeowners versus renters. It provides a breakdown based on fuel type, building type, and construction year. It also provides average monthly energy expenditures and energy burden (percentage of income spent on energy). HOW TO USE: The LEAD tool can be used to support program design and goal setting, and they can be paired with other data to improve LMI community energy benchmarking and program evaluation. Datasets are available for all 50 states, census divisions, and tract levels. You will have to enable macros in MS Excel to interact with the data. A description of each of the files and what states are included in each U.S. Census Division can be found in the file "DESCRIPTION OF FILES". For more information, visit: https://betterbuildingsinitiative.energy.gov/accelerators/clean-energy-low-income-communities; abstract: ABOUT THIS TOOL: The Better Building s Clean Energy for Low Income Communities Accelerator (CELICA) was launched in 2016 to help state and local partners across the nation meet their goals for increasing uptake of energy efficiency and renewable energy technologies in low and moderate income communities. As a part of the Accelerator, DOE created this Low-Income Energy Affordability Data (LEAD) Tool to assist partners with understanding their LMI community characteristics. This can be utilized for low income and moderate income energy policy and program planning, as it provides interactive state, county and city level worksheets with graphs and data including number of households at different income levels and numbers of homeowners versus renters. It provides a breakdown based on fuel type, building type, and construction year. It also provides average monthly energy expenditures and energy burden (percentage of income spent on energy). HOW TO USE: The LEAD tool can be used to support program design and goal setting, and they can be paired with other data to improve LMI community energy benchmarking and program evaluation. Datasets are available for all 50 states, census divisions, and tract levels. You will have to enable macros in MS Excel to interact with the data. A description of each of the files and what states are included in each U.S. Census Division can be found in the file "DESCRIPTION OF FILES". For more information, visit: https://betterbuildingsinitiative.energy.gov/accelerators/clean-energy-low-income-communities

  4. DOE LEAD -- Low Income Energy Affordability Data

    • zenodo.org
    json, pdf, zip
    Updated Jan 28, 2025
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    Catalyst Cooperative; Catalyst Cooperative (2025). DOE LEAD -- Low Income Energy Affordability Data [Dataset]. http://doi.org/10.5281/zenodo.14758685
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    zip, pdf, jsonAvailable download formats
    Dataset updated
    Jan 28, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Catalyst Cooperative; Catalyst Cooperative
    Description

    This archive includes the data behind the Department of Energy's (DOE) Low Income Energy Affordability Data (LEAD) tool. The LEAD tool is an online, interactive platform that helps users make data-driven decisions on energy goals and program planning by improving their understanding of low-income and moderate-income household energy characteristics. The LEAD Tool offers the ability to select and combine geographic areas (state, county, city and census tract) into one customized group so users can see the total area for their customized geographies (e.g., specific service territories). Archived from https://www.energy.gov/scep/low-income-energy-affordability-data-lead-tool

    This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

  5. r

    LEAD Tract Level

    • redivis.com
    Updated Jun 12, 2025
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    Carnegie Mellon University Libraries (2025). LEAD Tract Level [Dataset]. https://redivis.com/datasets/82z6-1fgs5gkva
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    Dataset updated
    Jun 12, 2025
    Dataset authored and provided by
    Carnegie Mellon University Libraries
    Description

    The table LEAD Tract Level is part of the dataset Low-income Energy Affordability Data, available at https://cmu.redivis.com/datasets/82z6-1fgs5gkva. It contains 84269 rows across 20 variables.

  6. NREL EFS -- Electrification Futures Study

    • zenodo.org
    json, zip
    Updated Jan 31, 2025
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    Catalyst Cooperative; Catalyst Cooperative (2025). NREL EFS -- Electrification Futures Study [Dataset]. http://doi.org/10.5281/zenodo.14782874
    Explore at:
    zip, jsonAvailable download formats
    Dataset updated
    Jan 31, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Catalyst Cooperative; Catalyst Cooperative
    Description

    The Electrification Futures Study (EFS) is a multi-year study conducted by NREL and its research partners—Electric Power Research Institute, Evolved Energy Research, Lawrence Berkeley National Laboratory, Northern Arizona University, and Oak Ridge National Laboratory. EFS used multiple analytic tools and models to develop and assess electrification scenarios designed to quantify potential energy, economic, and environmental impacts to the U.S. power system and broader economy. There are six reports comprising the EFS, with the final report released in May 2021. Archived from https://www.nrel.gov/analysis/electrification-futures.html

    This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

  7. Residential Patterns in South Florida

    • redivis.com
    application/jsonl +7
    Updated Mar 20, 2023
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    Carnegie Mellon University Libraries (2023). Residential Patterns in South Florida [Dataset]. https://redivis.com/datasets/78y1-bnxtd190k
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    application/jsonl, stata, spss, csv, sas, avro, parquet, arrowAvailable download formats
    Dataset updated
    Mar 20, 2023
    Dataset provided by
    Redivis Inc.
    Authors
    Carnegie Mellon University Libraries
    Time period covered
    Jan 1, 2016 - Dec 1, 2016
    Area covered
    South Florida, Florida
    Description

    Abstract

    This dataset was curated for the digital humanities portion of the project "500 Years of Black History in South Florida" by Synatra Smith, Luling Huang, and Portia Hopkins.

    Methodology

    Data was curated at the U.S. Census Tract level for four counties in South Florida: Broward, Miami-Dade, Monroe, and Palm Beach.

    There are two tables in this dataset:

    • sociodem_enepov: This table contains several sociodemographic variables and energy burden level at the census tract level;
    • airqua: This table contains monthly median air quality data at the census tract level for Year 2016.

    %3C!-- --%3E

    The sociodemographic data come from the American Community Survey (2020 5-year estimates). The variables include fraction of black population, median income, unemployment rate, and four education level variables for population 25 years or above: fraction of population below high school, fraction of population who had high school diploma only, fraction of population who had a college degree or equivalent only, and fraction of population who had a graduate degree. Here are the table numbers and relevant columns from the U.S. Census data portal:

    • Education: S1501
    • Black population: B01001B (column: B01001B_001E)
    • Total population: B01001 (for calculating fraction of black population)
    • Median income: S1903 (column: S1903_C03_001E)
    • Employment: S2301 (column: S2301_C04_001E)

    %3C!-- --%3E

    The energy burden data come from the U.S. Department of Energy's Low-Income Energy Affordability Data (LEAD) tool. The air quality (PM2.5 concentration) data come from the U.S. Centers for Disease Control and Prevention's Daily Census Tract-Level PM2.5 Concentrations, 2016.

    This project is conducted on behalf of the Association for the Study of African American Life and History and the National Park Service with additional funding from the Council on Library and Information Resources.

    References

    • Centers for Disease Control and Prevention. (n.d.). National Environmental Public Health Tracking Network [Data set]. www.cdc.gov/ephtracking

    %3C!-- --%3E

    %3C!-- --%3E

    • U.S. Census Bureau. (2023). United States Census Bureau: Data [Data set]. U.S. Department of Commerce. https://data.census.gov/

    %3C!-- --%3E

    Usage

    This dataset curates from data existing in the public domain and can be used for other purposes freely with attribution.

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U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (2025). Low-Income Energy Affordability Data - LEAD Tool - 2022 Update [Dataset]. https://catalog.data.gov/dataset/low-income-energy-affordability-data-lead-tool-2022-update
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Data from: Low-Income Energy Affordability Data - LEAD Tool - 2022 Update

Related Article
Explore at:
Dataset updated
Jan 22, 2025
Dataset provided by
United States Department of Energyhttp://energy.gov/
Description

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

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