Summary
Emitwise calculates your corporate GHG emissions using readily-available financial spend data from your company. This data covers all of your company’s purchases of goods and services, with similar expenses typically grouped into internal, hierarchical spend categories.
By mapping the spend categories used by your company to our central classification system, we estimate your GHG emissions by multiplying data on your purchased goods and services by industry-average emission factors that best reflect the kilograms of GHG emissions per dollar spent on the goods and services related to that spend category (e.g. average GHG emissions per dollar spent on computer equipment). Your GHG emissions are then automatically broken down by Scope 1 (direct), Scope 2 (indirect — purchased energy), and Scope 3 (indirect — value chain), in line with The Greenhouse Gas Protocol.
The approach of calculating GHG emissions from spend data at the spend category level is one of the fastest and simplest approaches to carbon accounting. It is easy for companies as it utilises data on financial spend that is already available, and it is a valuable, viable way to calculate a directionally-accurate GHG emissions baseline.
How do you calculate GHG emissions from spend data?
Each company is asked to map their internal spend categories to an entry in Emitwise’s central account classification (ECAC), our two-tier hierarchical spend taxonomy for use in carbon accounting. Note- it is Emitwise’s goal to automate this procedure. The data you provide us on how you classify your own internal spend will help us improve the accuracy of our automated solution.
Each ECAC spend category is mapped to an emission factor, reflecting the kilograms of GHG emissions per dollar spent on goods and services relevant to that spend category.
📝 The spend-based emission factors used at Emitwise are derived from EXIOBASE, a multi-regional environmentally-extended input-output (EEIO) database for estimating GHG emissions for industries in countries worldwide (source). Emitwise uses EXIOBASE rather than other national or multi-regional EEIO databases because it has the most granular detail at the industry and product levels, and that database was developed specifically for environmental assessments.
GHG emissions are calculated by multiplying the total amount spent per spend category by its corresponding emission factor. Emissions are then allocated among Scope 1, 2 and 3 based on the carbon accounting rules outlined in The Greenhouse Gas Protocol. For example, GHG emissions from purchased computer equipment will be allocated to Scope 3 Category 1 (Purchased Goods and Services), while GHG emissions from employee flights will be allocated to Scope 3 Category 6 (Business Travel).
How do you increase GHG emissions accuracy with spend data?
In some cases, Emitwise can estimate the quantity of goods or services purchased from the financial value of the transaction. This approach allows us to use higher-quality emission factors reflecting the average GHG emissions per unit of product purchased. Indeed, Emitwise will use a hybrid approach to calculate your Scope 1 and Scope 2 emissions to reduce the uncertainty in your GHG results.
To do this, Emitwise uses average market pricing data for products in a given spend category. For instance, the US Energy Information Administration (EIA) provides time series data on the average retail price of gasoline by month. For electricity in the US, pricing data from the state level are used, while datasets from the International Energy Association provide reputable quarterly pricing datasets at the national level for over 120 countries.
Emitwise uses this data to estimate the amount of fuel consumed or electricity purchased based on the spend data that you provide. As stated above, this price conversion to physical units will also allow for the application of rigorously validated physical emission factors for electricity and fuels. Doing so ensures that data gathering and submission is as seamless as possible for you as you will simply submit spend files without needing to collect additional physical unit data for other categories.