Emissions Data Exchange: Explained

James Baglia, a Senior Climate Analytics Lead at Persefoni, sheds light on the importance of emissions data exchanges in achieving accurate and comprehensive emissions measurements. James provides expert insights into the different calculation methods for scope 3 emissions and why collaboration and transparency across the value chain are needed to improve emissions data accessibility and promote a transition to a net zero economy.

The Scope 3 Data Challenge 

When it comes to calculating emissions, the GHG protocol provides a variety of calculation methods based on the source of emissions and the type of data available. Calculating scope 1 and 2 emissions is relatively simple, as the data required is often housed within the reporting organization and uses only a small number of straightforward calculation methods. For example, utility bills provide accurate measurements of electricity, heat, or steam consumption facility operations, enabling the measurement of scope 2 emissions. 

Scope 3 is where it gets more complex. Whereas scope 2 emissions are calculated by one of only two methods that cover both categories, each of the 15 scope 3 categories can be calculated by multiple different methods, with data varying in granularity and accessibility. Let's take category 1 - Purchased Goods & Services as an example, which offers three distinct calculation methods:

• Spend-based: This method estimates emissions based on what the user spends on a given service or good. It is often the simplest approach, as spend-based data is most easily accessible. However, it is the least accurate method as it assumes that any one good or service produces the same emissions, regardless of the manufacturer or provider.
• Average Data: This method estimates emissions based on the quantity of purchased material (e.g., kilograms of aluminum) and the corresponding material name, utilizing the average emissions associated with the production of that material. It provides higher accuracy compared to the spend-based method, although acquiring the necessary data may be less accessible.
• Supplier Specific: This method provides an estimate based on the quantity of purchased materials and supplier-specific product-level emission factors, commonly known as Product Carbon Footprints (e.g. from a life-cycle assessment). Although this method offers the highest level of accuracy, it relies on primary data that is often challenging to obtain.

Primary emissions data = increased footprint accuracy

Primary data direct from companies, while unfortunately not easily accessible, yields the most accurate emissions calculations. Not only is primary data important for the sake of accuracy, but it is paramount to the enablement of managing emissions, as it provides a more comprehensive view of emissions sources. Let’s look at scope 3 category 1, again, as an example. If an organization uses only spend-based calculations, the only way they could reduce their scope 3 Category 1 measured emissions is by reducing spend. However, a supplier-specific approach would offer more avenues for reduction, such as transitioning to more sustainable suppliers. These opportunities may not be captured through a spend-based approach or may have the opposite effect, as sustainable alternatives can sometimes incur higher costs.

Data Exchange as a solution

According to CDP, scope 3 emissions account for an average of 75% of an organization’s overall footprint. MSCI found that out of their ACWI IMI constituents, only 18% reported on their scope 3 emissions as of 2020. Although the latter number is on the rise, reaching 35% as of May 2023, it still indicates a significant number of emissions that remain unaccounted for. Considering the substantial portion of emitting activities falling under scope 3, calculating emissions across the 15 different categories, each with its own calculation methods and reliance on external data, can be a laborious task. 

This is where data exchange becomes critical. An emissions data exchange enables companies to share high-quality firsthand emissions data, including their scope 1 and 2 emissions. Access to this emissions data removes a massive hurdle for reporting organizations by easing the burden of having to “hunt” for your scope 3 emissions data, and provides easy access to the necessary data to make accurate calculations.

This exchange of emissions data enables accurate calculations of scope 3 data, but requires coordinated collaboration across the value chain. As the saying goes, a chain is only as strong as its weakest link. In this context, the accuracy of your measured emissions relies on the quality and accessibility of data from organizations within your value chain. Therefore, a collective effort to improve transparency, accuracy, and accessibility of emissions data is vital in the transition to a net zero economy.

As impossible as it may seem to produce a comprehensive and accurate calculation of an organization’s scope 3 emissions, it is feasible. As new technology enables interoperability across the value chain, this process of collecting high-quality primary data is becoming iteratively less burdensome. This positive trend will only continue as more companies join in the effort to enhance transparency. While it’s true that some calculation methods produce less-than-ideal measurements in terms of accuracy and actionability, they serve as a good starting point for organizations that are early in their decarbonization journey. The best thing a sustainability team or professional can do for their organization is to start somewhere, even if that means relying on spend-based data, and progressively adopting more granular calculation methods as better data becomes available. As I like to say, “crawl, walk, run.”