Commercial Buildings in Communities with Different Income and Racial Characteristics
A Comparison of Energy Efficiency and Fuel Sources – May 2022
- Executive Summary
- Section 1: Building Energy Performance
- By Race
- By Income
- Section 2: Fuel Source
- Distribution of All-Electric Buildings
- Sector Highlight: Electrification among Multifamily Housing
- Distribution of Heating Oil Use in Buildings
- Sector Highlight: Heating Oil among K-12 Schools
- Distribution of On-Site Solar Buildings
- Sector Highlight: On-Site Solar among K-12 Schools
DataTrends is an ongoing series of research and analysis from the U.S. Environmental Protection Agency (EPA) using data from the ENERGY STAR® Portfolio Manager® tool.
This analysis compares building performance, the prevalence of electrification, reliance on heating oil, and the use of on-site solar at buildings benchmarked in Portfolio Manager, across communities with different income and racial characteristics.
Using ENERGY STAR scores as a metric for building energy performance, the analysis shows that buildings overall in communities of color score an average of 2% lower than buildings in majority-white communities. Buildings in low-income communities score an average of 4% lower than those in moderate- and high-income communities. In low-income communities and communities of color, K-12 schools and multifamily housing buildings show the largest differences in ENERGY STAR scores compared to higher-income and majority-white communities, lower by roughly 9%.
The distribution of buildings that are all-electric, use heating oil, or have on-site solar may indicate how well positioned a community’s buildings are for achieving low-carbon operation. For communities in cold to moderate climates with the highest proportion of residents of color (greater than 75%) the data reveal the following relative to communities with fewer residents of color:
- The proportion of all-electric buildings is roughly 50% lower.
- Heating oil is used more frequently.
- The proportion of K-12 schools using heating oil is 2 to 3 times higher.
The data also revealed that, in both communities with a majority of low-income residents and a majority of residents of color, a lower proportion of K-12 schools have onsite solar.
DataTrends is an ongoing series of research and analysis from the U.S. Environmental Protection Agency (EPA) using data from the ENERGY STAR® Portfolio Manager® tool. Hundreds of thousands of buildings use Portfolio Manager to track their energy use. EPA periodically compiles and shares observations from this vast database, with the hope that the information will inform and advance public understanding of the commercial building sector. This analysis compares building performance, the prevalence of electrification, heating oil use, and the use of on-site solar at buildings across low-income communities and communities of color (as defined by U.S. census block group area parameters), for buildings benchmarked in Portfolio Manager.
Achieving an equitable and just transition to an energy efficient, low-carbon commercial building sector will require that the benefits of improved building performance and clean energy sources are distributed equitably across all communities. Particular attention is therefore paid to communities of color and low-income communities, which often encounter financial disinvestment and additional market barriers. EPA’s goal in developing this report is to inform discussions regarding policies and programs to achieve equitable performance and technology outcomes in the buildings that provide important services to the communities where they are located.
The all-buildings results in this report reflect data from the 85 building types included in Portfolio Manager. In addition, sector-specific observations are highlighted for the four commercial building types most frequently benchmarked using Portfolio Manager: K-12 schools, multifamily housing, offices, and retail stores. We include data for 242,098 buildings spanning all 85 building types in Portfolio Manager and encompassing over 20 billion square feet of floor space. The analysis of energy performance using the ENERGY STAR score is based on a subset of 160,033 buildings of 22 different types for which a 1-100 score was calculated in Portfolio Manager.
We merged the Portfolio Manager data with census block group-level data from the EPA’s Environmental Justice Screening and Mapping Tool, EJSCREEN, to create a merged dataset where buildings are organized based on demographic and socioeconomic characteristics of the communities in which they are located. There are a variety of indicators used by researchers to represent the demographic and socioeconomic characteristics of a population. The two EJSCREEN demographics used in this analysis are consistent with factors used across other EPA and U.S. government research efforts:
- Low Income: The percentage of a community’s residential population where the total income is less than or equal to twice the federal poverty level. We define a low-income community as a community where the majority of residents are low-income.
- Community of Color: The percentage of individuals in a community who list their racial status as other than white alone and/or list their ethnicity as Hispanic or Latino. That is, all people other than non-Hispanic, white-alone individuals. The word “alone” in this case indicates that the person is of a single race, since multiracial individuals are tabulated in another category – for example, a non-Hispanic individual who is half white and half American Indian would be counted as a person of color by this definition. This analysis defines a community of color as one where the majority (51 to 100 percent) of residents are people of color.
1To develop this report, data was pulled for all buildings in Portfolio Manager that benchmarked their energy use in 2019. We then applied the following filters to the dataset: source energy use intensity (EUI) between 5 and 2,000 kBtu/ft2, grid electricity use greater than 0 kBtu, site EUI greater than 0 kBtu/ft2, and building gross floor area greater than 1,000 square feet.
2A degree days-based climate filtering process was used to account for regional differences in the use of all-electric heating systems. See Appendix A for further details on the climate filtering process.
Limited public data is available on community demographics and commercial buildings, and Portfolio Manager contains information that can help to inform public understanding on this topic. However, we recommend that readers approach the findings with an understanding of the limitations of the data in Portfolio Manager and how they impact the results presented in this document:
- Data in Portfolio Manager is self-reported and largely unverified.
- Data may not be comprehensively representative of the national commercial building stock, all regions of the U.S., or of particular sectors.
- Results from the analysis of this data should not be assumed to reflect the national building stock.
- Data on energy costs are not required by Portfolio Manager, therefore the data available is insufficient to enable an evaluation of energy cost burdens in a manner that would parallel existing analyses of cost burdens in U.S. households.
- This analysis does not include comparisons of the buildings in Portfolio Manager to the total building stock within each community due to data limitations.
The analysis of all-electric buildings does not attempt to account for a broader range of considerations tied to beneficial electrification, such as the cost-effectiveness of various heating sources or specific technology choice decisions. We performed an analysis of cold and moderate climates, where fossil fuels are most commonly used for space heating, and a separate analysis of warm climates, where all-electric heating systems are more widespread and economically feasible due to lower heating loads.
Our analysis of Portfolio Manager data showed that, on average, buildings in communities of color have ENERGY STAR scores 1.3 points lower than all other buildings, a 2% difference.
Differences in average score based on race were statistically significant for all building types and for each of the building types listed on the graphs below.* K-12 schools and multifamily buildings show the largest differences in average ENERGY STAR scores, nearly a 9% difference.
* See Appendix B for details on the statistical tests used to evaluate score differences.
On average, buildings in low-income communities score 2.3 points lower than other buildings, a 4% difference.
Differences in average score based on income were statistically significant for all building types and for each of the building types listed on the graphs below.* Again, K-12 schools and multifamily housing buildings show the largest differences in average ENERGY STAR scores: nearly 9%.
* See Appendix B for details on the statistical tests used to evaluate score differences.
This analysis compares the prevalence of existing fully electrified buildings among communities. Importantly, the analysis does not include efficiency or cost data for electric heating or other end-use technologies.
In cold and moderate climates, the proportion of all-electric buildings in low-income communities is 4.7 percentage points lower than in moderate- and high-income communities. In warm climates, the difference is less than 1%.
Chart at left: In cold and moderate climates, the proportion of all-electric buildings is 5.4 percentage points lower among buildings in communities of color (as defined on page 4) compared to white communities. Within warm climates, the difference is 4%.
Chart at right: The average difference among communities is even greater when viewed by quartile. Just 11.5 percent of buildings in communities with 75-100 percent residents of color are fully electrified. This is substantially lower than the percentage of all-electric buildings in communities with fewer than 75 percent residents of color.
Multifamily buildings face unique electrification challenges and pronounced trends are noticeable in the data.
Chart at left: The data revealed a greater proportion of all-electric multifamily buildings in white communities compared to communities of color. In cold and moderate climates, the proportion of all-electric multifamily buildings in communities with a majority of residents of color is close to half the proportion in majority white communities.
Chart at right: In cold and moderate climates, the proportion of all-electric multifamily buildings in low-income communities is substantially lower than that in moderate and high-income communities. Conversely, in warm climates, the prevalence of all-electric buildings is slightly higher in low-income communities relative to moderate and high-income communities. The data revealed a weaker, but similar, socioeconomic trend for offices. No strong trends were found for the remainder of the building types analyzed (Appendix E).
Analysis of all Portfolio Manager buildings using heating oil in moderate and cold climates3 found that they are evenly distributed across communities with varying proportions of low-income residents (a 0.3% difference). However, use of heating oil is disproportionately concentrated in communities with a large percentage of residents of color (a 3.3% difference).
3A degree days-based climate filtering process was used to account for regional differences in the use of heating oil. See Appendix A for further details on the climate filtering process.
In communities in cold and moderate climates, with 75 to 100 percent residents of color, 11.5 percent of all buildings use heating oil, in contrast to buildings in communities with fewer than 75 percent residents of color, where heating oil usage ranges from 5.1 to 6.4 percent.
Chart at left: K-12 schools show the greatest differences among communities in heating oil use. In cold and moderate climates, the proportion of K-12 schools using heating oil is 1.5 percentage points higher in low-income communities than in moderate- and high-income communities, while the proportion using heating oil in communities of color is 11.5 percentage points higher—or more than double—than in white communities.
Chart at right: The analysis of data for K-12 schools in cold and moderate climates that use heating oil found that its use is disproportionately concentrated in communities with a high percentage of residents of color. Other building types exhibited weak trends in heating oil use across communities (Appendix E).
Data for all buildings show that use of onsite solar energy is evenly distributed across communities with varying proportions of low-income residents and residents of color.
Portfolio Manager data on K-12 schools show that both communities with a majority of low-income residents and majority of residents of color have a lower proportion of schools with onsite solar. Weaker socioeconomic trends emerged regarding onsite solar for the remainder of the building types analyzed (Appendix E).
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