The USGBC August 25, 2009 press release about their Building Performance Initiative implies that a large-scale collection of energy data from LEED® buildings will improve energy performance. This suggests a response to escalating criticism about the actual energy use of LEED® certified buildings compared with all others. Why do few published stories about these buildings include metered energy and water use data? If these buildings can waste energy efficiently, perhaps one answer is not to include those measures that allow that to happen.

The reality is that neither predicted nor actual measured energy use determines whether a building is energy efficient. Nor does energy use alone determine whether a building meets or exceeds all required or desired criteria, or provide the accountability necessary to achieve those results.

I have been collecting and evaluating detailed metered and measured building energy performance data for 40 years. Collecting the data is one thing, even if done completely and correctly. However, evaluating the data and then making comparisons among buildings is something else. Buildings alone do not use energy. The occupants, operators, and systems do.

In an extreme case, look at apartment buildings where each apartment is identical, and the metered energy use per apartment can easily vary by 2 or 3 to one, or more. Individually metered floors in office buildings occupied by the same company or tenant also can vary by 2 or 3 to one.

The functions in a building can also have a major influence on building energy use. The presence of a laundry in a hotel or hospital can make a 25 to 50% difference in total building energy use per bed, room, or square foot compared with an identical building on the same street.

Buildings with intermittent occupancy present similar dilemmas. How does one estimate, predict, or compare the energy data for two identical churches on the same block built at the same time, when one is only occupied for a few hours each Sunday and on some holidays, and the other is occupied most days of the week?

Comparing metered energy use to modeled energy data is not a valid measurement of anything. If the modeling and estimating methods were sufficiently accurate, utility companies would not require the use of meters.

Some articles I wrote 25 years ago show apartment by apartment or office floor by office floor metered energy use data in the same building. For another good example, look at the range of energy data for any given building type shown in the statistically significant quadrennial CBECS reports, collected at a cost in eight figures.

That reminds me of an energy research project 35 years ago during the 1970’s energy crisis. The US Postal Service spent hundreds of thousand of dollars instrumenting and recording the detailed energy use in a large postal facility. The conclusion was that they could collect lots of data.

The answer in evaluating and comparing energy data is using professional judgment and experience. That involves knowing and understanding not only the energy use and particulars of the subject building, but also the energy use and particulars of comparable buildings in the area. Comparing the energy use of a suburban office building in Boston with suburban office buildings in Providence without knowing the particulars is not likely to be meaningful or conclusive. This is much like the commercial real estate appraisal profession.

I think that there are a few important things to consider here. First, in USGBC’s Building Performance Initiative press release, LEED Senior Vice President Scot Horst notes that “[p]lenty of people are content to simply point to these longstanding issues [relating to LEED building performance] without offering a constructive way to address them. We’re going to take them on and engage practitioners and thought leaders alike in establishing a national roadmap to optimize building performance.”

After last fall’s Greenbuild, I suggested over at gbNYC that, if USGBC was serious about improving the energy performance of LEED buildings, it needed to engage building scientists such as Henry Gifford, Joseph Lstiburek, and Mr. Spielvogel in a meaningful way- certainly through more of an effort than simply collecting more data. As Mr. Spielvogel notes in his letter above, “[b]uildings alone do not use energy. The occupants, operators, and systems do.” This, of course, is what makes the type of predictive energy modeling on which LEED relies so imprecise and why project teams need to remain careful about the types of representations they make to their clients about the performance-related results of potential LEED certification. As Pat Murphy noted in a recent comment here at GRELJ, “[t]here is a crying need for accurate, verifiable and reliable energy rating systems. If LEED doesn’t fill the bill, other options will come forward.” I agree with Mr. Murphy and, in conclusion, would suggest that this is precisely what should give policymakers pause as they consider incorporating LEED- as currently constituted- into state- or local-level green building legislation.

• The Ugly, the Bad, & the Good: Thoughts on Greenbuild 2008 (gbNYC)
• Some Buildings Not Living Up to Green Label (NYT)
• Building Performance Initiative (USGBC Press Release)

Specifically, while the new Stadium was projected to more or less play the same as the old one across the street, a number of factors that the Yankees and their design team may not have considered, underestimated, or were outside of their control all along have resulted in a drastically different performance than the club anticipated. For example, the new Stadium stands sixty feet taller and concourses on each level of seating are exposed to the building’s exterior, which may be creating a wind tunnel effect that is blowing baseballs out towards the fences. Interestingly, the Yankees and their engineers are not entirely certain about what will happen to these wind patterns once the old Stadium is razed as demolition has yet to start in earnest.

The analogy here, of course, is where policymakers, owners, or other stakeholders make legislative or project-related choices that are based on projections which do not accurately reflect actual performance once a structure is brought online; these dangers are even more acute where contract documents obligate a project team to achieve a certain level of performance or fixed reduction in operating expenses that are based on a predictive model. The reasons why a building’s performance could diverge may be complex and entirely unanticipated by stakeholders; building science is complicated and buildings themselves are complex systems for which modeling does not always reflect reality. The experience at New Yankee Stadium to date may be a rather simplistic example, but I do think it helps make the point that predicting performance and evaluating performance based on actual data are two very different ballgames.