— ASSET PORTAL GUIDE —

Seamlessly report your environmental performance data

As part of the Performance component of the 2020 GRESB Real Estate Assessment, participants are required to report information at both portfolio and asset level.

The GRESB Asset Portal enables participants in the GRESB Real Estate Assessment to report environmental performance data at the asset level either via the GRESB Asset Spreadsheet or by connecting to the GRESB Asset API.

The indicators are then aggregated to complete the Performance Indicators aspect in the GRESB Real Estate Assessment.

See guidance on using the GRESB Asset Spreadsheet
Learn more about API connections in our API documentation.

How to use the GRESB Asset Portal

To help you make the most of the GRESB Asset Portal, we have created a video which covers the most important steps for your submission:

Visit the GRESB Asset Portal

Visit https://portal.gresb.com/ and login with your user credentials, or create an account by clicking “Sign up for GRESB“.
Visit your Assessment Portal and select the entity for which you would like to manage assets.
Select “Assets” in the right hand navigation.

Upload Data

If you have opted to connect your data management system to the GRESB Asset Portal via the API, or you are working with a GRESB Data Partner, this step will be taken care of automatically.

1. Download the GRESB Asset Spreadsheet and enter your data. See guidance on using the GRESB Asset Spreadsheet

Important! If you entered data in a previous year and wish to edit your existing assets. Please click “Export Data to Excel“. This will provide you a pre-populated GRESB Asset Spreadsheet with your entity’s assets.

2. Click “Upload Assets in Excel” to upload your spreadsheet.

Important! To create a new asset in the GRESB Asset Portal, leave the field GRESB Asset ID empty. To update an existing asset, enter the asset’s ID into the column GRESB Asset ID. Assets with a duplicate or non-existent ID will be rejected.

3. You will receive an email once the import has been processed. You may leave or refresh the page at any time. Please note, if you upload a new spreadsheet while we are processing an import for you, your import will be overwritten with the latest upload.

Asset Data Validation

There is a comprehensive set of validation rules implemented for asset-level reporting. These rules consist of logical checks on the relationships between different data fields in the Asset Portal. These errors appear in red around the relevant fields in the Asset Portal Data Editor, along with a message explaining the error. Participants cannot aggregate their asset data to the portfolio level, and therefore cannot submit their Performance Component, until all validation errors are resolved.

The Data Editor is designed to help participants report on their assets correctly. Certain fields are grayed out when they are not relevant for reporting. For instance, all landlord-controlled fields are grayed out if the option “Whole Building is Tenant Controlled” is selected. Any data in grayed-out fields will be ignored by the Portal on aggregation to the portfolio level.

Types of validation checks

Checks for existence

All fields marked “mandatory” in the asset spreadsheet must be present.
If the building is owned and operational for any part of the reporting year, the Floor Area Covered and the Maximum Floor Area corresponding to this building’s performance data are expected to be reported for Energy, GHG, Water, and Waste. Data Availability and Vacancy Rate must also be present.

Checks on dates against the reporting year

Dates must be within the reporting year (either fiscal or calendar, set in EC4)

Logical checks on operational control

If the option “Whole building is Tenant Controlled” in Reporting Characteristics is selected, then “Whole Building” in the Energy tab cannot be unselected
If “Whole building is Tenant Controlled” is selected, then only the data in the corresponding Whole Building fields for energy and water are relevant for reporting. Any data in the Base Building + Tenant Space fields will be ignored.

Logical checks between floor areas

Any Maximum Floor Area field must be less than or equal to the Asset Size.
Any given Floor Area Covered field must be less than or equal to the corresponding Maximum Floor Area.
The sum of Maximum Floor Area fields for Energy, GHG, and Water must be greater than or equal to the Asset Size.

Comparisons between Consumption/Emission and Floor Area Covered

If consumption values are reported, then the corresponding Floor Area Covered field must be present and greater than zero.
If a Floor Area Covered is reported, then the corresponding Consumption/Emission field must be present.

Specific rules for Energy

If reporting on Base Building + Tenant Space, the Maximum Floor Areas reported must be less than or equal to the asset sizes per subspace
- Example: the Maximum Floor Areas for Common Areas must be less than or equal to the total Common Area floor area
The Renewable Energy consumed or purchased by landlord must be less than or equal to the sum of all of the consumption values in Landlord Controlled fields

Specific rules for GHG emissions

There are checks between the Maximum Floor Area and Covered Floor Area fields in the Energy and GHG tabs.
- Example: If the Whole Building is Tenant Controlled, then only Scope 3 fields are allowed to be present in the GHG tab. In this example, the Maximum Floor Area must be equal to the Asset Size, and the Floor Area Covered must be less than or equal to the smaller of the sum of the Floor Areas Covered reported in the Energy tab or the GHG Scope 3 Maximum Floor Area.

Specific rules for Water

Consumption and floor areas can be present for either Whole Building or Base Building + Tenant Space, but not both
Reused and recycled water purchased off-site must be less than or equal to the sum of the reported consumption values

Specific rules for Waste

If the Data Coverage is larger than zero, then the Hazardous and Non-hazardous Waste consumption fields must be present
The sum of the proportions of waste by disposal routes must equal 100%

Based on statistical modelling, GRESB identifies outliers in reported performance data for selected indicators in the Real Estate Performance Component. This analysis is performed to ensure that all participating entities included in the benchmarking and scoring process are compared based on a fair, quality-controlled dataset.

The model is built to detect outliers at the asset level. Outliers are flagged in the GRESB Asset Portal so that participants can check their input data, and make corrections if necessary.

Outliers are only calculated for data points without validation errors, so outliers will not be present in the Portal until after participants resolve any errors from automatic validation.

Model

There are two kinds of outliers flagged by the Portal: Intensities and Like-for-Like (LFL) change in consumption/emission. Outliers are flagged per asset, for the following data types:

Indicator	Data Type	Outlier Checks
EN1	Energy	Intensity (kW/m2) Like-for-Like consumption change (%)
GH1	GHG	Intensity (tonnes/m2) Like-for-Like consumption change (%)
WT1	Water	Intensity (m3/m2) Like-for-Like consumption change (%)
WS1	Waste	Intensity (tonnes/m2)

Outliers are only calculated for data that is eligible for inclusion in scoring. For example, LFL outliers are only calculated for assets and data types that are eligible for LFL inclusion in scoring. Intensity outliers are only calculated if the reported Floor Areas Covered are greater than 0.

The two most common explanations for outliers in the past related to vacancy and data availability period. The 2020 GRESB Outlier Model takes both Vacancy Rates and Data Availabilities into account when calculating outlier values.

Intensity values are normalized by both vacancy and data availability.
The consumption values that go into the LFL change calculations are normalized by vacancy. LFL outliers are not normalized by data availability because an asset is only eligible for LFL inclusion if the data availability is 2 continuous years.

Thresholds

For LFL outliers, the thresholds for detecting outliers vary between 20 – 30%, based on the previous year’s consumption value. These thresholds are based on analysis of asset-level data from previous years.

For Intensity outliers, the thresholds for detecting an outlier vary by data type and property type. They are based on a combination of analysis of data from previous years and market research on typical Energy, GHG, Water, and Waste use per property type.

The lower and upper thresholds for Intensities are listed for all property types and data types on the Asset Portal Guidance.

Property Type	Energy (kWh/m^2)		GHG (tonnes/m^2)		Water (m^3/m^2)		Waste (tonnes/m^2)
	lower	upper	lower	upper	lower	upper	lower	upper
Retail: High Street	40	800	1e-5	0.4	1e-4	5	1e-5	0.4
Retail: Retail Centers: Strip Mall	40	800	1e-5	0.4	1e-4	5	1e-5	0.4
Retail: Retail Centers: Shopping Center	40	800	1e-5	0.4	1e-4	5	1e-5	0.4
Retail: Retail Centers: Lifestyle Center	40	800	1e-5	0.4	1e-4	5	1e-5	0.4
Retail: Retail Centers: Warehouse	10	400	1e-5	0.3	1e-4	2	1e-5	0.2
Retail: Restaurants/Bars	10	800	1e-5	0.4	1e-4	5	1e-5	0.4
Retail: Other	10	800	1e-5	0.4	1e-4	5	1e-5	0.4
Office: Corporate: Low-Rise Office	80	600	1e-5	0.4	1e-4	4	1e-5	0.3
Office: Corporate: Mid-Rise Office	80	600	1e-5	0.4	1e-4	4	1e-5	0.3
Office: Corporate: High-Rise Office	80	600	1e-5	0.4	1e-4	4	1e-5	0.3
Office: Medical Office	20	600	1e-5	0.4	1e-4	4	1e-5	0.3
Office: Business Park	1	400	1e-5	0.2	1e-4	2	1e-5	0.2
Office: Other	1	800	1e-5	0.4	1e-4	4	1e-5	0.3
Industrial: Distribution Warehouse	10	400	1e-5	0.2	1e-4	2	1e-5	0.2
Industrial: Industrial Park	1	400	1e-5	0.2	1e-4	2	1e-5	0.2
Industrial: Manufacturing	10	400	1e-5	0.3	1e-4	3	1e-5	0.4
Industrial: Other	1	400	1e-5	0.3	1e-4	3	1e-5	0.4
Residential: Multi-Family: Low-Rise Multi-Family	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Residential: Multi-Family: Mid-Rise Multi Family	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Residential: Multi-Family: High-Rise Multi-Family	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Residential: Family Homes	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Residential: Student Housing	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Residential: Retirement Living	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Residential: Other	40	600	1e-5	0.3	1e-4	4	1e-5	0.3
Hotel	40	800	1e-5	0.4	1e-4	5	1e-5	0.3
Lodging, Leisure & Recreation: Fitness Center	20	600	1e-5	0.3	1e-4	4	1e-5	0.3
Lodging, Leisure & Recreation: Indoor Arena	20	600	1e-5	0.3	1e-4	4	1e-5	0.3
Lodging, Leisure & Recreation: Performing Arts	20	600	1e-5	0.3	1e-4	4	1e-5	0.3
Lodging, Leisure & Recreation: Swimming Center	20	600	1e-5	0.3	1e-4	4	1e-5	0.3
Lodging, Leisure & Recreation: Museum/Gallery	20	600	1e-5	0.3	1e-4	4	1e-5	0.3
Lodging, Leisure & Recreation: Other	20	600	1e-5	0.3	1e-4	4	1e-5	0.3
Education: School	1	800	1e-5	0.4	1e-4	5	1e-5	0.4
Education: University	1	800	1e-5	0.4	1e-4	5	1e-5	0.4
Education: Library	1	800	1e-5	0.4	1e-4	5	1e-5	0.4
Education: Other	1	800	1e-5	0.4	1e-4	5	1e-5	0.4
Technology/Science: Data Center	5000	8000	1e-5	3	1e-4	5	1e-5	0.2
Technology/Science: Laboratory/Life Sciences	5000	8000	1e-5	3	1e-4	5	1e-5	0.2
Technology/Science: Other	5000	8000	1e-5	3	1e-4	5	1e-5	0.2
Healthcare: Healthcare Center	80	800	1e-5	0.4	1e-4	4	1e-5	0.3
Healthcare: Senior Homes	80	800	1e-5	0.3	1e-4	4	1e-5	0.3
Healthcare: Other	80	800	1e-5	0.4	1e-4	4	1e-5	0.3
Mixed use: Office/Retail	10	800	1e-5	0.4	1e-4	5	1e-5	0.4
Mixed use: Office/Residential	10	800	1e-5	0.4	1e-4	5	1e-5	0.4
Mixed use: Office/Industrial	1	800	1e-5	0.4	1e-4	5	1e-5	0.4
Mixed use: Other	1	800	1e-5	0.4	1e-4	5	1e-5	0.4
Other: Parking (Indoors)	1	400	1e-5	0.2	1e-4	3	1e-5	0.2
Other: Self-Storage	10	400	1e-5	0.2	1e-4	3	1e-5	0.2
Other	1	800	1e-5	0.4	1e-4	5	1e-5	0.4

Validation

Outliers are validated automatically based on the thresholds. Detected outliers do not require explanations from the participant. However, participants will have the opportunity to optionally select reasons for each outlier. This information is for reporting purposes only.

There are two levels of automatic outlier validation.

If an outlier is detected above the fixed threshold, then the data points associated with that outlier will be included in scoring. However, they will not be included in the creation of the scoring benchmark quantiles for scoring data coverage and LFL changes.
If the outlier is substantially higher than the upper threshold (more than 1000 times greater), the data points associated with that outlier will be rejected. That is, they will not be included in scoring.

Common mistakes that can lead to outliers

An outlier may result from a reporting mistake. When outliers are flagged, make sure to check the Consumption/Emission, Floor Area Covered, Vacancy Rate, and Data Availabilities for your asset.

Common reporting mistakes that result in Intensity outliers:

Using the wrong unit (e.g. MWh instead of kWh) or wrong conversion factor
Reporting full Floor Area Covered when the consumption data is incomplete; for instance, missing tenant consumption data or missing fuel consumption.
Reporting on occupancy instead of vacancy
Reporting a full year of Data Availability, when the consumption data is not captured for the full reporting year

Common reporting mistakes that result in LFL outliers:

Reporting consumption data for the current reporting year and no consumption data for the previous year, with the same data coverage
Reporting a full year of Data Availability for both this year and the previous year, when the consumption data is not actually captured for a full two reporting years
Reporting on occupancy instead of vacancy, or reporting the same vacancy year over year when it actually changed

Contact a GRESB Data Partner

If you would like to integrate your data with our API, please contact a GRESB Data Partner in your region.

Energy Profiles Limited

INNAX GEBOUW & OMGEVING

July 4, 2017

LORD Green Strategies

UL EHS Sustainability

July 4, 2017

Verco Advisory Services Limited

July 4, 2017

GRESB Asset Portal

— ASSET PORTAL GUIDE —

Seamlessly report your environmental performance data

How to use the GRESB Asset Portal

Types of validation checks

Model

Thresholds

Validation

Common mistakes that can lead to outliers

Contact a GRESB Data Partner

Directory

Resources

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