David Hsu is a Penn IUR faculty fellow and assistant professor of City and Regional Planning in the School of Design.
Buildings—particularly large commercial buildings and multi-family residential buildings—are a significant source of energy use and greenhouse gas emissions in the United States. In fact, commercial buildings alone account for 20 percent of all domestic energy consumption and greenhouse gas emissions—a statistic that points to the urgency of promoting energy efficiency in the building sector. To this end, over the past few years, policymakers, academics, the real estate industry, and the environmental community in the United States have all begun to converge on a single policy mechanism for improving energy efficiency in buildings: benchmarking, or the reporting of energy performance for existing buildings.
Seven U.S. cities – New York, Austin, San Francisco, Seattle, Washington DC, Minneapolis and Philadelphia— as well as two states (WA and CA), have passed such policies to improve energy efficiency. Boston is presently considering this legislation, and other major U.S. cities are expected to follow later this year.
Benchmarking is a way to improve the energy efficiency of individual buildings, as well as a way to transform the market for energy efficiency retrofits. Benchmarking is, at its heart, an information policy that requires building owners to disclose the energy use of their building, either to the public (as in NYC and SF), or to prospective buyers and tenants (as in Seattle and Austin). By introducing information about energy use to all parties at the time that they are negotiating the price and valuation of buildings, benchmarking is intended to transform the market for energy efficiency by eliminating the information asymmetries that disincentivize owners to invest in energy efficient buildings, systems, and retrofits that would otherwise be highly lucrative asset improvements.
Benchmarking differs from other building information policies in that it measures the actual operating performance of existing buildings. Asset rating policies, such as USGBC’s LEED system and others, are based either on a pre-set scale of points for various design features, or the performance of the building modeled by engineers. There are, however, two problems with these policies. First, point systems and building models often fail to accurately predict the actual operating performance of buildings. Second, these systems don’t incentivize building owners to implement operational changes, like training cleaning staff and security guards to turn off the lights in unoccupied offices at night, which can often be the cheapest and most effective way to reduce energy use.
Benchmarking is also a fairly cost-effective way to measure building energy performance, compared to a more detailed engineering audit. Benchmarking for a typical NYC building, which consists of gathering previous years of utility bills and making some basic building measurements, runs between $500 and $1000. In comparison, a detailed engineering audit and analysis can cost $50,000 or more. My current research indicates that benchmarking data is a highly cost-effective way to predict the different patterns of energy use between buildings, and provides a sufficiently detailed baseline for building managers and owners to work towards improvement.
Furthermore, a number of city governments are finding that benchmarking policies are an important new source of data for analysis. I am currently engaged in two data analysis projects with the cities of New York and Seattle in order to improve the quality of their data and to better inform the real estate sector in those cities on trends in energy use. For example, I recently worked with New York City to analyze benchmarking data collected as part of Local Law 84, which requires all privately-owned properties with individual buildings over 50,000 square feet or with multiple buildings with a combined square footage over 100,000 square feet to annually measure and report their energy and water use. (Read the report here). Creating city-specific datasets provides a basis for more meaningful peer group comparisons, where an owner in New York City can judge his or her building against similar buildings.
As benchmarking spreads, and the real estate industry has access to more information about how energy is used in buildings, we can expect to see continued changes. Building owners and tenants will better understand their own energy use, and opportunities to reduce it. Governments and utilities may use benchmarking data in a more targeted way to better aim their existing incentives and subsidies for energy efficiency. Third-party software companies are already being founded to provide building owners and policymakers with higher quality data and analysis of buildings.
Benchmarking is a relatively new policy, but is growing and maturing quickly. Still, as with many other areas of society that are being transformed by data, the opportunities for building energy efficiency have just begun.