How Benchmarking Data Can Help Cities Meet Climate Goals

Cities have set aggressive greenhouse gas reduction targets over the past few years. One of the most aggressive is Fort Collins, Colorado, which is targeting up to an 80 percent reduction by 2030, with interim benchmarks along the way. As deadlines draw nearer and the climate risks to urban centers grow, city leaders are feeling a heightened sense of urgency to slash emissions more quickly to get on track with their stated goals.

When it comes to reducing carbon use in cities, the biggest and most cost-effective impact will always come from improving the energy efficiency of buildings, which provides returns well above market rate. The challenge is that it is also one of the most challenging to measure, especially at the level of individual buildings.

To reduce city-wide emissions to the levels required by stated goals, cities will need to start by curbing the energy appetite of buildings—the biggest end-users of electricity. And, to most effectively address the built environment, they’ll need better data. 

The Importance of Benchmarking Data

Both public and private entities could use existing benchmarking and energy use disclosure data to reduce greenhouse gas emissions from buildings and maintain positive financial returns, but to date such data has been underutilized and only 18 U.S. cities have benchmarking and energy use disclosure programs in effect. In locations where benchmarking and disclosure has already been established, that data is one of the most readily available sources that can be used by cities, utilities, service providers, and technology developers to drive energy use and greenhouse gas emissions reductions.

While energy disclosure is helping drive dramatic changes, today’s use cases are just the beginning of an efficiency revolution that will be driven by big data in buildings. Cities report that benchmarking and disclosure has contributed up to a 2.4 percent reduction in building energy use per year—a small step toward the larger city goals. To make the building energy use revolution possible, we need more universal, more granular, and more holistic data. Below is a snapshot of how this data is being used today, and the changes that could dramatically increase the impact of these policies.

Current Benchmarking and Disclosure Data Applications

So, what can U.S. cities do with their data? Here are a few examples of progressive benchmarking data applications in the U.S. and abroad:

  • Outcome-based energy codes: Germany’s building energy code, EnEV, is an outcome-based code that prescribes an annual energy use intensity threshold to prove compliance. Ongoing compliance is recognized with an Energy Performance Certificate. Seattle has piloted outcome-based codes, and included an optional performance path in its energy code as well. Benchmarking and disclosure can help cities inform such performance-based codes to ensure that the energy use intensity requirements are accurate and feasible.
  • Energy disclosure at point of sale or lease: In the EU, Energy Performance Certificates are required to be updated and made publically available in residential or commercial buildings at the time of sale or lease. As a next step, the UK has been considering requiring properties to achieve a minimum energy performance to be transacted or leased.
  • Studies of potential energy savings across building types: New York City’s Technical Working Group Report analyzed the city’s benchmarking data to develop typical typologies based on building age, size, and use type. With information about HVAC systems and these defined typologies, the analysis team ran scenarios to identify energy conservation measures that would reduce building energy use 40–60 percent with existing technologies.
Next Step: Asset Data

Existing benchmarking and disclosure data typically collects annual energy use by fuel type, square footage, and some high-level building characteristics, like the year of construction. If the goal of benchmarking data is to highlight areas for savings within a given group of buildings, there is room for improvement on the types of data collected.

One of the most critical pieces missing from benchmarking and disclosure data is any kind of asset data. How old is the HVAC equipment? When was the last window replacement? That type of data could be used to monitor and determine which building components should be targeted by policies, incentives, workforce training, and even local technology development. Additionally, it can be used by analysts to determine bespoke and cost-effective retrofit packages for individual buildings.

Asset data disclosure programs should:

  • Focus on large assets that are easily reportable and responsible for most loads
  • Bundle reporting with building construction or renovation applications to reduce the administrative burden
  • Begin with voluntary opt-in disclosures that come with a benefit (e.g., faster access to utility or city incentives), but transition to opt-out with a penalty (e.g., reduced access to utility incentives) over time

Without this type of detailed asset data, it will become increasingly difficult to manage existing building energy use within cities.

Next Step: Data Granularity

Because this data is often publically available, building a repository for building asset data and energy use data can help to engage the private sector as well. Private sector companies have been developing data analytics platforms and business models to aid building owners in implementing energy savings strategies, which can be fueled by publically available data.

Current data analytics platforms track monthly energy use and monitor energy costs over time, which, although useful, does not always provide actionable information to building owners. A few platforms run analytics to identify energy efficiency projects, and although their number is growing, there is still a need for further project identification strategies.

Benchmarking data that collects asset data in addition to more granular interval data could be leveraged in a much more powerful way, especially as the interaction between the buildings and the grid becomes more interactive. Substituting smart-meter data for standard monthly meter data as part of benchmarking reporting could lead to much more sophisticated trend analysis and energy efficiency measure identification. This data would be especially useful for private companies as they develop their analytics. And even if this data is not made publically available, it would be useful to cities as they carry out analyses to gain a deeper understanding of energy time of use and grid resiliency.

Call to Action

Rocky Mountain Institute believes strongly that the momentum gained by benchmarking and disclosure ordinances is a step in the right direction. In recent months, RMI has worked with cities and real estate portfolios across the U.S. to help them achieve their greenhouse gas emission reduction goals. From our lessons learned, we hope that these suggested improvements will encourage cities to expand and refine the scope of their data collection to make that data truly actionable. Cities and states need to collect data that will help define or justify action, because as greenhouse gas reduction deadlines grow nearer, the need for action is imminent.

Image courtesy of iStock.