GRESB’s Estimation Model and GHG calculation methodology

Today, many asset managers struggle to accurately measure and report on their GHG emissions because critical data is missing, such as asset-level energy consumption.

GRESB Members that participate in the Real Estate Assessment can take advantage of highly accurate estimations of missing energy and GHG data using the GRESB Estimation Model (GEM), which draws on a global database of roughly 170,000 individual assets. In these cases, accurate asset estimations are critical to understanding a portfolio’s transition risk and when tackling SFDR reporting.

So how do we accurately calculate complete GHG intensities for real estate portfolios?

GRESB uses the most representative data available, whether this is reported directly by a participant or statistically derived, to calculate GHG emissions for whole assets and, by extension, that of complete real estate portfolios, regardless of how much energy or GHG data is available as input.

The methodology GRESB uses to calculate GHG intensity of a portfolio is aligned with global standards, such as the GHG Protocol’s Accounting and Reporting Standard for Corporates and the PCAF Global Standard, and consists of:

  1. Estimating missing energy consumption data
  2. Converting data into absolute GHG emissions
  3. Calculating and aggregating GHG intensities

GRESB takes particular care when providing estimations and dealing with imperfect cases with an aim to retain the integrity of the physical reality that the information is trying to reflect. This approach follows commonly accepted frameworks and standards and is transparent in a way that is easily understood and supported by the industry.

Step 1: Estimating missing energy consumption data

The first step to calculating GHG emissions for GRESB Members is to fill any gaps in energy consumption data for the full building.

We start by identifying how much of the data for a given asset has been reported. It is very important to track and disclose how much energy data, and subsequently calculated GHG data, is estimated. Otherwise, there is no indication of the data quality of the final metric, which reduces not only the confidence in the final output but also the incentive to continue measuring and gathering high-quality data in the future.

Next, we estimate the remaining energy consumption of a given floor area using the GRESB Estimation Model (GEM). To do this, we use a weighted mix of (a) the energy intensity of the reported data for that floor area type and (b) a median intensity for that property subtype and country, which is derived from about 170,000 individual assets contained in the GRESB benchmark.

GEM uses the most granular data available. If data is reported at the whole building level, the estimation procedure is conducted at the whole building level. If data is reported at the subspace level, the estimation procedure is conducted at the floor area type level.

For example, if a GRESB Member is missing energy consumption data for the tenant’s portion of a multifamily midrise building in Amsterdam, the model can drill down and compare the building’s known data points – like floor size, location and specific property subtype – against the GRESB database. Because we have detailed data from a large enough pool of similar buildings, we can construct a representative median intensity to provide a truer picture of the missing data while avoiding the effects of outliers.

The figure below is based on a blind test comparing GRESB’s asset estimation against an alternative estimation based on linear extrapolation. As you can see, the GRESB estimation is far closer to ‘true’ than a standard alternative approach.

Step 2: Converting data into absolute GHG emissions

At its most basic, GHG emissions associated with a particular amount of energy may be calculated by multiplying that amount of energy (measured in kWh) with the emissions factor (EF, a conversion factor with the unit kgCO2e/kWh) associated with the specific energy source.

GHG emissions = energy consumption * emissions factor

For all reported data, the energy consumption is multiplied by the energy type–specific EF for its reported energy type – electricity, fuel, or district heating and cooling.

Estimated energy consumption data is multiplied by a combined emissions factor that is designed to more accurately reflect the combination of energy types that supply the remaining floor area.

For assets with no reported energy consumption data, the estimated GHG emissions is derived from the GRESB Estimation Model – the product of the reported floor area, the average energy intensity for the asset type, and a GRESB-derived combined emissions factor for that asset.

Treatment of Renewable Energy

This methodology follows the location-based method as described in the GHG Protocol Corporate Accounting and Reporting Standard*. As such, renewable energy that is generated off-site is not counted toward the reduction of GHG emissions.

For the calculation of GHG emissions, renewable energy generated and consumed on-site is subtracted from reported building electricity consumption.

Exported renewable energy is not subtracted from the building’s energy energy consumption before calculation of the GHG emissions. This is consistent with the GHG Protocol’s Scope 2 Guidance**. Exported renewable energy is not included in the GHG emissions calculation in any way.

Step 3: Calculating and aggregating GHG intensities

The calculation of GHG intensity is done by dividing absolute GHG emissions (kgCO2e) by the floor area (m2), over which the corresponding energy was consumed. Asset-level GHG intensities can be aggregated to portfolio-level GHG intensities by taking the floor area–weighted average of the asset-level intensities.

With that you have a complete, globally applicable, portfolio-level understanding of GHG-intensity that uses the most granular data available for any reported or estimated data.

The GRESB methodology provides a number of benefits. It:

  • Works for all assets and property subtypes globally
  • Takes advantage of the most granular level of GRESB reporting with GHG emissions built-up from energy data reported for each floor area type
  • Leverages GRESB’s global database of real estate assets to estimate missing data with the most representative sample possible
  • Serves real estate assets for which no energy consumption data is provided


GHG methodology in action

The GRESB Estimation Model is used in both the GRESB Transition Risk Report and the SFDR Reporting Solution for real estate.

If you’re interested in a more detailed breakdown of the methodology – complete with edge cases, formulas, and GRESB variables – you can find it in the Appendix of the Transition Risk Report.

See GEM for SFDR

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* GHG Protocol The Greenhouse Gas Protocol A Corporate Accounting and Reporting Standard: Revised Edition. Online.

** “For accurate scope 2 GHG accounting, companies shall use the total—or gross—electricity purchases from the grid rather than grid purchases “net” of generation for the scope 2 calculation. A company’s total energy consumption would therefore include self-generated energy (any emissions reflected in scope 1) and total electricity purchased from the grid (electricity). It would exclude generation sold back to the grid.” GHG Protocol Greenhouse Gas Protocol. GHG Protocol Scope 2 Guidance: An Amendment to the GHG Protocol Corporate Standard. Online.