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Housing and Climate Resource Library

Energy Resources

This page is about the fuel used for cooking and heating appliances and communities’ energy burden. Some kinds of fuel, like gas used for cooking, can create hazards in the indoor air.

Relevant variables for this topic include energy burden, fuel combustion, and fuel most used in households.

Datasets/Data Explorers

Climate Central’s Coastal Risk Screening Tool
Climate Central’s Coastal Risk Screening Tool is an interactive map that predicts coastal flooding and sea level rise using advanced global models. The tool provides several maps, including one that shows affordable housing at risk of flooding by decade. The maps are based on peer-reviewed science and include big datasets, which are large volumes of structured and/or unstructured data.

  • Dataset owner: Climate Central.
  • Dataset update frequency/maintenance: Unknown.
  • Dataset jurisdictions included: This screening tool covers about 170 countries including the United States.
  • For each variable: Coastal Flood Risk Maps. Since the mapping of coastal flood risks within the United States is collected by the National Oceanic and Atmospheric Administration (NOAA), it is assumed that the U.S. data for the variables below is provided by the NOAA. For data outside of the United States, the Coastal DEM is used to model land elevation. Maps are based on the latest sea-level projections, including the Sixth Assessment Report (AR6) from the Intergovernmental Panel on Climate Change (IPCC) and the 2022 Sea Level Rise Technical Report from an interagency U.S. government task force.
    • Name of variable: Time horizon.
      • What the variable measures: Sea level rise and coastal flood threats by decade.
      • Variable source(s): NOAA, 2022 (United States only).
    • Name of variable: Water level.
      • What the variable measures: What areas will be impacted by different water levels.
      • Variable source(s): CoastalDEM v2.1 and NOAA, 2022 (United States only).
    • Name of variable: Warming choices.
      • What the variable measures: A comparison of long-term sea leave rise based on different pollution pathways.
      • Variable source(s): CoastalDEM v2.1 and NOAA, 2022 (United States only).
    • Name of variable: Temperature.
      • What the variable measures: Looks at the effects that different warming events could have on sea level rise in the future decades.
      • Variable source(s): Leading Consensus (IPCC 2021).
    • Name of variable: Elevation data.
      • What the variable measures: Uses elevation data to show sea level rise and coastal flooding risk.
      • Variable source(s): CoastalDEM v2.1 and NOAA, 2022 (United States only).
    • Name of variable: Ice sheets.
      • What the variable measures: How lost ice in Antarctica and Greenland will impact the world.
      • Variable source(s): CoastalDEM v2.1 and NOAA, 2022 (United States only).
    • Name of variable: Affordable housing.
      • What the variable measures: How coastal flooding puts affordable housing at risk.
      • Variable source(s): National Housing Preservation Database and NOAA, 2022.
    • Name of variable: Coastal wetlands.
      • What the variable measures: How wetlands resiliency is impacted by sea level rise, coastal development, and marsh vertical growth.
      • Variable source(s): NOAA, 2022 (United States).

Studies

Multidimensional Housing and Environmental Quality Index (HEQI)
The Multidimensional Housing and Environmental Quality Index (HEQI) is a one-time research study that was developed based on the World Health Organization’s Housing and Health Guidelines and used the 2019 American Housing Survey (AHS) data. The study provides information on residential environment exposure that can be used to inform strategies to address climate change. HEQI included multiple dimensions of healthy housing with the use of 10 domains: fuel combustion, dampness and mold, pests and allergens, lead paint, high indoor temperatures, low indoor temperatures, crowding, injury hazards, inadequate water and sanitation, and ventilation. The final version of the HEQI included 43 AHS variables across the 10 domains. Dampness and mold, low indoor temperatures, household crowding, and inadequate water and sanitation were the four most documented domains.

  • Dataset owner: Produced by authors affiliated with George Washington University, Tufts Medical Center, Penn State University, and Harvard University. Published in Environmental Health in 2022.
  • Dataset update frequency/maintenance: HEQI was produced in a one-time study.
  • Dataset jurisdictions included: The American Housing Survey and other national surveys were used to develop the national HEQI.
  • Specific climate and housing variables:
    • Name of variable: Fuel combustion.
      • What the variable measures: The AHS did not specifically ask about combustion activities. The study used the presence of cooking and heating appliances with fuels such as gas, wood, and kerosene as surrogates for actual use.
      • Variable source(s): The data were approximated using available data from AHS or external sources.
    • Name of variable: Household crowding.
      • What the variable measures: The AHS did not specifically ask about household crowding. The crowding indicator identified households with 1.5 or more persons per rooms, per U.S. Census and HUD’s definition of severe crowding.
      • Variable source(s): The data were approximated using available data from AHS or external sources.
    • Name of variable: Lead exposure.
      • What the variable measures: The AHS did not specifically ask about lead exposure. Study identifies lead paint risk in pre-1980 housing units with peeling paint larger than 8 inches by 11 inches.
      • Variable source(s): The data were approximated using available data from AHS or external sources.
    • Name of variable: High indoor temperatures.
      • What the variable measures: The AHS did not specifically ask about periods of high temperature. Households are identified with high indoor temperature if the household did not have central air or window air conditioning unit(s). U.S. Census regions were controlled since geographic regions and climate types can vary.
      • Variable source(s): The data were approximated using available data from AHS or external sources.
    • Name of variable: Ventilation.
      • What the variable measures: The AHS did not specifically ask about ventilation factors such as insulation or building leakage. This variable was approximation of building leakage, a measurement of building envelope airtightness relative to its size and heights.
      • Variable source(s): The data were approximated using available data from AHS or external sources. This indicator was determined by the adaptation of methods from Chan et al. (2013) and accounted for year built, unit size and height, basement and foundation types, the International Energy Conservation Code (IECC) Climate Zone Map, and the 2009 Residential Energy Consumption Survey.
    • Name of variable: Dampness and mold.
      • What the variable measures: Mold and water leaks in the last 12 months in various places in the home.
      • Variable source(s): AHS.
    • Name of variable: Pests and allergens.
      • What the variable measures: Daily or weekly evidence of rodents or cockroaches.
      • Variable source(s): AHS.
    • Name of variable: Low indoor temperatures.
      • What the variable measures: Twenty-four hours or more when the unit was uncomfortably cold.
      • Variable source(s): AHS.
    • Name of variable: Injury hazards. 
      • What the variable measures: Electrical and structural integrity.
      • Variable source(s): AHS.
    • Name of variable: Water quality and quantity.
      • What the variable measures: Unit has no hot/cold running water, unit without running water in the last 90 days, and non-public drinking water sources.
      • Variable source(s): AHS.
    • Name of variable: Poor sanitation.
      • What the variable measures: One or more toilet breakdowns within the last two months that lasted six hours or more; one or more sewer breakdowns within last three months that lasted six hours or more; unit has no bathtub, shower, or flushing toilet; and unit does not have a working kitchen sink.
      • Variable source(s): AHS.

Surveys

American Community Survey
The survey is administered by the U.S. Census Bureau and provides yearly data on jobs and occupations, veterans, homeownership, renters, and other community topics in the United States. This survey provides one- and five-year estimates. The results of the American Community Survey, can be accessed here. These data provide valuable insights into demographics, housing, employment, and more.

  • Dataset owner: U.S. Census Bureau.
  • Dataset update frequency/maintenance: New data is collected annually.
  • Dataset jurisdictions included: The survey covers the entire U.S.
  • What can this dataset and variable(s) tell us about climate and housing impacts? This survey helps public officials, planners, and community members learn of the current needs, challenges, and opportunities and provides data that can influence future and support to need communities and activities. The survey answers could indicate climate impact, system vulnerabilities (to extreme weather events), and potential indoor air quality (IAQ) issues.
  • Specific climate and housing variables (for each variable: survey questions):
    • Name of variable: Which fuel is used most for heating this house, apartment, or mobile home?
      • What the variable measures: The 2021, five-year national percentages of each fuel used to heat a house.
      • Variable sources: Survey respondents.
    • Name of variable: What is the annual payment for fire, hazard, and food insurance on this property?
      • What the variable measures: The annual payment for fire, hazard, and food insurance.
      • Variable sources: Survey respondents.

 

Latest page update: May 7, 2025.