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The desire for a spacious home has been pushing average single-family square footage up in recent decades. Yet, over the last 120 years the average floor space per home has remained surprisingly steady. While the population has increased, household size has fallen and the resulting increase in number of homes has pushed total floor space on an upward trajectory. Enlarge Image.

Results: To understand U.S. building energy use and determine energy conservation opportunities in those spaces, researchers must understand the amount of floor space currently built. Toward that end, Pacific Northwest National Laboratory researchers developed the first consistent, long-term historical time-series of new U.S. construction, housing stock, and floor space. Having access to a long-term data set is fundamentally important for understanding building energy consumption, and how it might evolve in the future.

Analyzing the data, the researchers determined that from 1890 to 2010 the evolution of floor space is strongly coupled to changes in household size: in the last 120 years, floor space increased ten times, while population increased only five times. This number is explained by a dramatic halving of the number of persons per household during the period.

Why It Matters: To get an idea of residential energy use in the United States, just count the number of buildings. Or, to be more precise, measure the total floor space in those buildings. That's because 20 percent of the total U.S. energy consumption and energy-related carbon dioxide emissions comes from homes, apartments and other residential buildings. That data is important for understanding energy consumption, and is especially useful for energy use predictions. This work provides future research with a valuable data set to understand residential building energy consumption trends and what they might imply for the future.

Methods: The PNNL researchers, working at the Joint Global Change Research Institute (JGCRI), used an inventory modeling approach to estimate housing stock by age cohort from data on the number of new buildings constructed and total building stock over time. They employed survival dynamics in the time-series, separated by building type and age. This data set allows for increased accuracy in the estimation of the drivers of long-term residential energy consumption. Their estimation method was designed to minimize the effect of inconsistent and incomplete data in the various available survey datasets.

This research highlights the fact that, in addition to population growth, household size can be a key factor driving residential building floor space trends. Furthermore, in many studies where floor space data has been missing, GDP (gross domestic product-an indicator used to gauge a country's economic health) has been considered a driver of floor space. This study indicates that, for the United States at least, the long-term relationship between floor space and GDP has been relatively stable (aside from periods of substantial socio-economic disruption such as the great depression and World War II).

Residential floor space change compared to population growth. Variables are normalized to 1 beginning in 1891, so y-axis is unitless. Average floor space per home has stayed steady, despite growth in population and total floor space. Graph courtesy of the authors.

The long-term floor space data developed in this study provides fundamental input for energy modeling. The study also offers valuable context for future energy consumption projections. The study systematically documents the survey data used in the estimation, providing future research with a valuable new data set.

What's Next? The new methodology aids the development of housing unit and floor space time series for large countries. This will be particularly useful in countries with a rapidly growing urban population and where data is lacking, such as China. This detailed data set for the United States can also be used in retrospective evaluation studies using energy-economic and integrated assessment models, such as the Global Change Assessment Model (GCAM).

Acknowledgments

Sponsor: This research was supported by the Office of Science of the Department of Energy (DOE) as part of the Integrated Assessment Research Program (IARP). The GCAM model used in this study was developed at PNNL with base funding support from the DOE's Office of Science, IARP.

Research Team: Maria Cecilia P. Moura, Steven J. Smith, and David B. Belzer, for PNNL working at the JGCRI, a collaboration between PNNL and the University of Maryland.

Research Area: Climate and Earth Systems Science

Reference: Moura MCP, SJ Smith, and DB Belzer. 2015. "120 Years of U.S. Residential Housing Stock and Floor Space." PLOS ONE 10(8): e0134135. DOI: 10.1371/journal.pone.0134135

January 4, 2016