Location-based emission factor methodology

This article documents Scaler's methodology for location-based emission factors, including dataset sources, regional application logic, projection calculations, and version management. This serves as the authoritative technical reference for auditors, methodology reviewers, and advanced users.

For step-by-step configuration instructions, see Configuring location-based emission factors.

For version history and dataset changes, see Location-based emission factor reference log.

Location-based emission factors represent the average emissions intensity of the electricity grid or energy supply in a specific geographic region. Scaler provides a default, regularly updated emission factor set combining multiple authoritative sources to enable consistent emissions calculations across global portfolios.

What this article covers:

Scaler draws location-based emission factors from the following authoritative datasets:

CRREM (Carbon Risk Real Estate Monitor)

Australian National Greenhouse Accounts (NGA)

U.S. EPA eGRID (Emissions & Generation Resource Integrated Database)

Energy Star Portfolio Manager

Scaler creates a reference set by combining factors from multiple datasets. The current default set is labeled using this naming convention:

CRREM v2.07 + EPA + NGA + ESPM

This indicates:

Each reference set is documented with specific dataset versions and publication dates in the Location-based emission factor reference log.

Scaler applies emission factors at different geographic levels depending on dataset availability and user configuration:

National-level factors (default for most countries)

Regional factors (Australia and United States)

Australia: State-level or electricity market region

United States: eGRID subregion

Even when an Energy network is assigned for Australia or USA assets, users can still choose to use the CRREM data sets in these countries with the gear icon under Data Collection Portal → Portfolio → Emission Factors.

For Australia and the United States, Scaler can apply regional emission factors that better reflect the actual emissions intensity of the electricity grid serving a specific asset. This improves accuracy for:

Australia has two main wholesale electricity markets:

National Electricity Market (NEM)

Wholesale Electricity Market (WEM)

How Scaler applies regional factors:

If Energy network is assigned → Scaler uses the state or market region emission factor from Australian NGA.

If Energy network is not assigned → Scaler uses the national-level factor.

The U.S. EPA divides the country into 26 eGRID subregions based on electricity transmission networks. Each subregion has a unique emissions profile depending on generation mix.

Examples:

Determining your eGRID subregion:

Users can identify the correct subregion using:

How Scaler applies subregional factors:

If Energy network is assigned → Scaler uses the eGRID subregion emission factor from EPA eGRID.

If Energy network is not assigned → Scaler uses the national-level factor (U.S. average).

Energy networks are configured at the asset level in Asset Details → Location.

The Energy network field only appears when Country is set to Australia or United States.

For bulk updates, use the Scaler Spreadsheet with the field name exactly matching: Energy network.

Sources:

Scope classification:

Projections: Available through 2050 using CRREM grid decarbonization rates.

Sources:

Calculation methodology:

No globally standard database exists for district heating and cooling emissions. Scaler follows CRREM, GRESB, and GHG Protocol guidance:

DHC_EF = ELECTRICITY_EF × 0.876340396

Where:

Why this approach:

District heating and cooling systems often use electricity as a primary energy input (heat pumps, chillers). The conversion factor represents the efficiency relationship between electricity input and thermal energy output.

Historical context:

Previously, CRREM applied this conversion to the previous year's electricity emission factor. Scaler (as well as CRREM since v2.06) applies it to the same year for methodological clarity and consistency.

Scope classification:

Projections: Available through 2050 (derived from electricity projections).

Heat-cold storage systems convert electricity into stored thermal energy (heating or cooling capacity). Scaler calculates emission factors using a Coefficient of Performance (COP) approach.

Calculation methodology:

COP = ENERGY_OUTPUT / ELECTRICITY_INPUT

Higher COP values mean less electricity per unit of heat/cold produced, lowering emissions.

Per kWh output:

EF_OUTPUT = EF_ELECTRICITY / COP

Where:

Example:

With an electricity emission factor of 0.300 kg CO₂e/kWh, the heat-cold storage emission factor per kWh output is:

0.300 / 4.9 = 0.0612 kg CO₂e/kWh

Scope classification:

Projections: Available through 2050 (derived from electricity projections).

Sources:

Natural gas:

Other fuels:

District hot water / chilled water:

Scope classification:

Why fuels appear in the Location-based Emission Factor Tool:

Although fuels contribute to Scope 1 emissions (not Scope 2), they appear in the Location-based Emission Factor Tool to provide a single interface for reviewing and managing all default emission factors across energy types. This does not change their scope classification.

Important: Fuels do not have a location-based vs market-based divide.

Fuel emission factors are based on physical combustion properties and should only be adjusted when actual fuel composition differs from standard values (e.g., biogas blends). See the section Why fuels appear in the Location-based Emission Factor Tool for guidance on when adjustments are appropriate.

Projections: Not available, the same emission factor is used for all years through 2050. Fuel combustion rates are expected to remain relatively stable, and so no forward-looking fuel emission factor changes are applicable.

For datasets without forward-looking projections (e.g., EPA eGRID, Australian NGA), Scaler uses CRREM's grid decarbonization rates to interpolate emission factor values through 2050.

This appears in downloads and references as "Dataset_name (CRREM projections)".

Scaler applies decarbonization rates to:

Interpolation process:

Example:

Projections available:

Projections NOT available:

Why only electricity-based projections:

CRREM's pathways focus on grid decarbonization—the transition of electricity generation from fossil fuels to renewable energy. Fuel combustion emission factors are not expected to change significantly over time.

Roadmaps Tool:

CRREM stranding risk analysis:

At any time, users can switch to manual emission factors to:

Requirements when using manual overrides:

Visual cues:

Audit trail:

The Reference field should be used to document the source of manual values to maintain GHG Protocol compliance and audit readiness.

For instructions, see Configuring location-based emission factors.

Scope classifications in Scaler are determined by the control boundary (landlord vs tenant) set in Area type combined with the resource Subcategory (electricity, fuel, etc.), not by which tool displays the emission factor.

Scope 1 — Direct emissions under landlord control

Scope 1 includes emissions that:

In Scaler, this includes:

Scope 2 — Indirect energy emissions under landlord control

Scope 2 includes emissions that:

In Scaler, this includes:

Scope 2 emissions can be calculated using:

Scope 3, Category 3 — Tenant-controlled operational emissions

In Scaler's real estate analytics, Scope 3 refers specifically to operational emissions occurring on-site but under tenant control.

This includes:

Key principle:

Control is determined explicitly by the selected Area type, which specifies whether the activity is landlord-controlled or tenant-controlled. The same resource (e.g., natural gas) can be Scope 1 or Scope 3 depending on control.

For comprehensive scope guidance, see Understanding Scope 1, Scope 2, and Scope 3 emissions in Scaler.

The Location-based Emission Factor Tool displays emission factors for all energy Subcategories present in your portfolio, including:

This design allows users to review default factors and apply manual overrides consistently across all energy sources in a single interface.

The location-based vs market-based distinction applies only to Scope 2 emissions (purchased electricity, steam, heat, and cooling) under the GHG Protocol.

Fuels do not have a location-based vs market-based divide.

Fuel emission factors are based on the physical combustion properties of the fuel itself, which are consistent globally (with minor variations for fuel composition). For example:

Fuel emission factors in the Location-based Emission Factor Tool should only be manually adjusted when:

The actual fuel composition is physically different, resulting in different combustion emissions.

Examples:

When NOT to adjust fuel emission factors:

Why this matters:

Adjusting fuel emission factors without a legitimate change in fuel composition can:

If your organization uses a fuel with a different composition (e.g., biogas blend, alternative fuel mix), you can:

This maintains audit trail transparency while accurately representing physical combustion emissions.

Scaler updates the default emission factor set when authoritative sources release new data. However, updates follow a structured approach:

General rule: Scaler avoids updating default emission factors during active reporting seasons (January–July) to maintain consistency for organizations preparing sustainability reports, GRESB submissions, and compliance filings.

Exceptions: Critical corrections or data quality issues may necessitate mid-season updates. These are communicated to portfolio administrators ahead of time.

Default sets:

Previous emission factor sets:

Audit trail:

For complete version history, see Location-based emission factor reference log.

Users can choose previous versions from the Emission Factor Tool dropdown. This is useful for: