With this new tool from Climate Cabinet Education, discover which parts of your community have the potential to maximize the benefits of the historic federal climate investments from the Inflation Reduction Act. Areas meeting key eligibility criteria will qualify for even greater levels of funding.

Search For Your Community

Enter the name of a state, county, municipal utility, or rural electric cooperative to view its Justice40 communities, distressed zip codes, energy communities, and designated low-income census tracts on an interactive map. You’ll also see descriptions of which programs are available and how much bonus eligibility parts of your community can access.

Tax Credit Programs

NameAgencyBase Benefit
Direct Pay clean energy INVESTMENT tax creditsIRS6-30% (based on labor standards and material sourcing requirements)
Direct Pay clean energy PRODUCTION tax creditsIRS.55 cents/kwh - 2.75 cents/kwh (based on labor standards and material sourcing requirements)
Solar For AllBased on grant application
Alternative Fuel Refueling Property CreditIRS6-30% (based on labor standards and material sourcing requirements)
Neighborhood Access & Equity GrantDOTup to 80% covered


Administrative Boundaries

Boundaries for counties, states, zip codes, and U.S. territories were extracted from TIGER/Line Shapefiles corresponding to the 2020 U.S. Census. The data may be accessed through the U.S. Census Bureau’s web tool or FTP server.

Distressed Communities

Distressed zip codes were obtained by downloading and filtering a CSV data file from the latest release of the Economic Innovation Group’s Distressed Communities Index (DCI). The release uses the U.S. Census Bureau’s Business Patterns and American Community Survey 5-Year Estimates for 2016-2020. Zip codes identified as “distressed” by EIG were then merged with 2020 TIGER/Line zip code Shapefiles from the U.S. Census Bureau to produce the final dataset.

Electric Retail Service Territories

Shapefiles for rural cooperatives and municipal utilities were downloaded from the Homeland Infrastructure Foundation-Level Data (HIFLD) open data portal, hosted by the Geospatial Management Office of the U.S. Department of Homeland Security. The data, which may also be viewed on an alternative web map, was last published on December 9, 2022, and utilizes multiple data sources from different years (e.g., state GIS portals, Energy Information Administration Tiger/Line Shapefiles).

Energy Communities

Two datasets for coal closure and fossil fuel employment qualifying energy communities were downloaded from the Energy Data eXchange, hosted by the Department of Energy’s National Energy Technology Laboratory (NETL). The data was last updated on June 15, 2023. At present, two categories of energy communities under the Inflation Reduction Act (IRA) have been made publicly available through the platform:

1. Census tracts and directly adjoining tracts that have had coal mine closures since 1999 or coal-fired electric generating unit retirements since 2009.

2. Metropolitan statistical areas (MSAs) and non-metropolitan statistical areas (non-MSAs) that have had for at least one year since 2009, 0.17% or greater direct employment related to extraction, processing, transport, or storage of coal, oil, or natural gas (the fossil fuel employment (FFE) threshold) and have an unemployment rate for 2022 that is equal to or greater than the national average unemployment rate for 2022.

The coal closure and FFE-eligible datasets were downloaded as zipped Shapefiles, filtered to include only geographies qualifying as energy communities, and then merged together to create the final dataset.

Justice40 Communities

A Shapefile containing metadata and geographic boundaries for Justice40 Communities was directly downloaded from the Climate & Economic Justice Screening Tool (v.1), last updated on November 22, 2022. The Council on Environmental Quality, Executive Office of the President, which manages the tool, used 2010 census tracts for boundaries and 2015-2019 American Community Survey (ACS) demographic data to determine which tracts were classified as “disadvantaged” for at least one of eight criteria: climate change, energy, health, housing, legacy pollution, transportation, water and wastewater, and workforce development.

Low-Income Communities

According to statute (26 USC §45D(e)), low-income communities (LICs) are defined as: “any population census tract if— ‘(A) the poverty rate for such tract is at least 20 percent, or ‘(B)(i) in the case of a tract not located within a metropolitan area, the median family income for such tract does not exceed 80 percent of statewide median family income, or ‘(ii) in the case of a tract located within a metropolitan area, the median family income for such tract does not exceed 80 percent of the greater of statewide median family income or the metropolitan area median family income. Subparagraph (B) shall be applied using possessionwide median family income in the case of census tracts located within a possession of the United States.”

To identify low-income census tracts for the web map, an analysis conducted by ESRI was replicated. TIGER/Line Shapefiles (2020) for nationwide census tracts were downloaded from the U.S. Census Bureau’s web server and and 2016-2020 American Community Survey data was exported from Social Explorer for tables “B17020: Poverty Status in the Past 12 Months” and “Table B19113: Median Family Income in the Past 12 Months (in 2020 inflation-adjusted dollars)” at the tract, metropolitan statistical area, and state geography levels. A Python script was then executed to merge and filter the data to produce the final dataset.


To estimate populations in specific geographic regions, we utilized the population-weighted centroids of Census Block Groups from the 2020 United States Census. Block groups are subdivisions of census tracts, typically holding 600 to 3,000 people. Block groups allow for a more fine-grained approach to population estimates since population densities can vary within a single census tract.

If a block group’s population-weighted centroid fell within a particular geography, we attributed its entire population to that area. Both census tracts and block groups respect state and county boundaries. However, census tracts and block groups may cross zip codes, municipal utility, and/or rural cooperative boundaries.

When estimating populations for intersecting areas — for example, the number of inhabitants in a Justice40 community served by Coles-Moultrie Electric Cooperative — we allocated the full population of any block groups whose population-weighted centroid was in the overlapping region. If the population-weighted centroid was not in the intersecting area, we did not allocate any of the population to the overlapping area.

We compared two different methodologies for calculating population using census block groups. In one methodology, we calculated the percentage area of a block group that intersected with a specific geography, and we allocated that percentage of the block group’s population to that geography. In the other methodology, we allocated the entire population of a block group to a specific geography if the population-weighted centroid was inside of that geography. The area allocated population methodology is much more computationally expensive than the population-weighted centroid methodology.

To test the difference between the two methodologies, we used a paired T-test with 1,100 samples. To pick our sample size, we used an estimated effect size of 0.1, a significance level of 0.05, and a power of 0.9. The T-statistic was -0.36 and the p-value was 0.72, which indicates that the differences in methodologies are not statistically significant. Based on this, we used the less computationally expensive population-weighted centroid methodology.