Scope 3 Financed Emissions Databases


MAISY Zip Code Emissions Databases Provide Scope 3 Financed Emissions Estimates for Residential Mortgages and Commercial Real Estate Loans

Quick Takeaway: Easiest Scope 3 Financed Emissions Data Development. Send us a list of your mortgagors and commercial real estate customer loans with ZIP code, and other loan information and we will send you a database of detailed GHG financed emissions for each ZIP and for the entire financial institution along with an emissions intensity statistic that adjusts for changes in customer population characteristics with an indexing methodology used by the US Department of Commerce.

If you prefer to send us summary/aggregate data to compile emissions and emissions intensity, no problem. We will work with whatever customer data you can provide. See info below.

MAISY Scope 3 ZIP Code Databases provide detailed emissions data for residential single family owner occupied dwelling units and commercial real estate loan customers in each ZIP code area in the continental US.

These data are developed from the widely used MAISY Utility Customer ZIP-Level Resdential and Commercial Energy Use Database comprised of data on more than 7 million utility customers. Financial institutions provide individual customer loan data or ZIP averages with whatever customer segment detail is available (see below) and Jackson Associates provides detailed emissions data for each ZIP code and a consolidated emissions report for the financial institution.

Jackson Associates also uniquely provides an emissions intensity statistic that applies a methodology drawn from economic theory which adjusts for changes in customer geographic and household characteristics to minimize reported emissions biases. This methodology is used by the US Department of Commerce in price index calculations and is a well-accepted approach to account for the kind of computational complexity inherent in the emissions index.

Mortgage Information Provided by the Financial Institution

Two options are available:
  1. Loan data for each individual customer:
    Customer ZIP code (required)
    Customer income (optional)
    Customer dwelling unit floor space (optional)
    Other customer information (e.g. dwelling unit age, optional)
    Current loan balance (optional but recommended)
    Origination loan amount (optional but recommended)

    -- or --

  2. Customer loan data by ZIP code:
    Number of mortgages within the ZIP Code Area (required)
    or Option 2: Number of mortgages within the ZIP Code Area by 3 income categories
    or Option 3: Number of mortgages within the ZIP Code Area by 3 floor space categories
    or Option 4: Number of mortgages within the ZIP Code Area by 9 income/floor space income categories
    Attribution factor(s) (ratio of the outstanding mortgage balance at the time of GHG
    accounting to the property value at loan origination) matching detail provided with selected option 1-4, (optional but recommended)


Commercial Real Estate Loan (CRE) Information Provided by the Financial Institution

Two options are available:
  1. Loan data for each individual customer:
    Customer ZIP code (required)
    Customer business category (optional but strongly recommended)
    Customer building floor space (optional but strongly recommended)
    Current loan balance (optional but recommended)
    Origination loan amount (optional but recommended)

    -- or --

  2. Customer loan data by ZIP code:
    Number of CRE loans within the ZIP Code Area (required)
    or Option 2: Number of CRE loans within the ZIP Code Area by business category
    or Option 3: Number of CRE loans within the ZIP Code Area by building floor space categories
    or Option 4: Number of CRE loans within the ZIP Code Area by business category/building floor space categories
    Attribution factor(s) (ratio of the outstanding CRE loans balance at the time of GHG
    accounting to the property value at loan origination) matching detail provided with selected option 1-4, (optional but recommended)

Data Items: ZIP Code Scope Financed Emissions Databases
(Data provided for each ZIP code)

VARIABLE GROUPING DATA ITEMS
LOCATION INFORMATION ZIP Code
ZIP Name
County & State
Metro Area
Emissions Data Items Calculated for Each ZIP Code
MORTGAGE EMISSIONS DATA Total Annual Emissions (CO2e) (including emissions generated by household electricity,
natural gas, fuel oil and propane use)
CO2 Emissions
CH4 Emissions
N2O Emissions
HFCs Emissions
PFCs Emissions
SF6 Emissions
NF3 Emissions
GHG Intensity Data (see the whitepaper Avoiding Scope 3 Financed Emissions Data Development Pitfalls )
COMMERCIAL REAL ESTATE LOAN EMISSIONS DATA Total Annual Emissions (CO2e) (including emissions generated by commercial firm electricity,
natural gas, fuel oil and propane use)
CO2 Emissions
CH4 Emissions
N2O Emissions
HFCs Emissions
PFCs Emissions
SF6 Emissions
NF3 Emissions
GHG Intensity Data

Data Items: Consolidated Financed Emissions Data
(Sum of all ZIP-level data )


VARIABLE GROUPING DATA ITEMS
  Total Number of Morrtgages
Total Number of Commercial Real Estate Loans
Total Financial Firm Emissions Data
MORTGAGE EMISSIONS DATA Total Annual Emissions (CO2e) (including emissions generated by household electricity,
natural gas, fuel oil and propane use)
CO2 Emissions
CH4 Emissions
N2O Emissions
HFCs Emissions
PFCs Emissions
SF6 Emissions
NF3 Emissions
GHG Intensity Data (see the whitepaper Avoiding Scope 3 Financed Emissions Data Development Pitfalls )
COMMERCIAL REAL ESTATE LOAN EMISSIONS DATA Total Annual Emissions (CO2e) (including emissions generated by commercial firm electricity,
natural gas, fuel oil and propane use)
CO2 Emissions
CH4 Emissions
N2O Emissions
HFCs Emissions
PFCs Emissions
SF6 Emissions
NF3 Emissions
GHG Intensity Data


Methodology Summary

MAISY Scope 3 mortgage emissions estimates are provided for each ZIP code area and as a total for all ZIP areas serviced by each financial institution.

MAISY Scope 3 mortgage emissions estimates are developed by applying the MAISY ZIP Code Utility Customer Energy Use Database by multiplying (1) the number of financed residential mortgages in each ZIP code by (2) average ZIP single family/duplex electricity kWh, fuel oil, natural gas and propane use (by customer segment if available), and by (3) fuel-specific EPA emissions factors for that ZIP code.

The easiest and most cost effective way to develop these required data is for the financial institution to provide us with data on each individual mortgagor including ZIP code and any available energy-related customer information including household income, floor space, etc. We then match these loan customers to customers in the MAISY Databases to estimate energy use and resulting emissions.

If the financial institution prefers to provide ZIP average information (option 2 above) the number of mortgagors in the ZIP code is used along with ZIP average energy use and emission information. If the financial insitution is able to provide the number of mortgagors in customer segments (income, floor space), this detail is used in computing energy use and emissions providing more accurate emissions estimates.

The PCAF standard requires multiplying these emissions totals by an attribution factor, which is equal to the ratio of the outstanding mortgage balance at the time of GHG accounting to the property value at loan origination. If the financial client provides this data for individual mortgagors or for the ZIP code and/or for customer segments in the ZIP code, these attribution factors are applied to reflect reported emissions only attributable to the financial institution. Otherwise, reported emissions data can be adjusted by the financial institution to recognize the attribution factor.

ZIP code-detail is crucial for accurate accounting of financed emissions as there is significant variation in ZIP-average energy use and resulting emissions. For financial institutions that have mortgage investments across even sub-state regions, variations in emissions factors resulting from variations in electric generation fuels use, can also be significant.

The proposed rule requires emissions reporting in terms of GHG intensity to provide “context to a registrant’s emission in relation to its business scale.” The rule emphasizes the importance of being able to compare the value of the GHG intensity over time to assess the extent to which a financial institution is meeting its goals. The problem with this approach for financed emissions is that (1) year-to-year weather variations, (2) geographic variations in emissions associated with new mortgage originations (as much as a factor of 4 or more) and (3) variations in new mortgage originations floor space (i.e., size of dwelling units) can create a picture of increasing SCOPE 3 GHG emissions intensity even though a GHG intensity adjusted for these factors would show a reduction in emissions. See a recent whitepaper titled Avoiding Scope 3 Financed Emissions Data Development Pitfalls which describes this issue in more detail and provides several procedures compatible with the proposed rule and based on long-standing economic index theories and practices.

The paper offers a new price-index based methodology drawn from economic theory that adjusts for changes in customer geographic and household characteristics to minimize biases in reported emissions statistics. This methodology is used by the US Department of Commerce in price index calculations and is a well-accepted approach to account for the kind of computational complexity inherent in the emissions intensity statistic.

The easiest and most cost effective way to develop Scope 3 commercial real estate (CRE) emissions estimates is for the financial institution to provide us with data on each individual CRE loan including ZIP code, business category and floor space (if available). We then match these loan customers to customers in the MAISY Databases to estimate energy use and resulting emissions.

If the financial institution prefers to provide ZIP averaage information (option 2 above) MAISY Scope 3 commercial real estate (CRE) emissions estimates are developed by multiplying (1) the number of CRE loans by general business type category in each ZIP code (provided to us by a financial institution client) by (2) average ZIP business category electricity kWh, fuel oil, natural gas and propane use, by (3) EPA emissions factors for that ZIP code. If the financial institution client is able to provide number of loans in floor space segments the average CRE energy use averages and resulting emissions estimates are calculated based on average energy use within each segment.

As with residential mortgage financed emissions, ZIP code-detail is crucial to accurate accounting of CRE emissions as there is significant variation in ZIP-average energy use and factors that can create significant missinformation regarding financial firm CRE emissions GHG index over time. Reference the link above to see a discussion and appropriate approach to providing a CRE emissions GHG index that accounts for these issues.

Finally, MAISY Scope 3 Database results will be modified to be consistent with final SEC rules that are expected to be announced after June 17, 2022.

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