Yesterday, the Philadelphia Eagles beat the Kansas City Chiefs in the NFL championship game. Now a global event marked on everyone’s calendar, consumer spending on The Big Game was forecast to hit a whopping $18.6bn. 

But what about the cost to the planet? According to the National Retail Federation (NRF), consumers will fork out on food and drink (81%), team apparel or accessories (14%), television (10%), furniture (6%), and decorations (8%) for the match. Producing all these items means producing emissions. 

Using Lune’s emission intelligence to enrich spend data from the NRF’s report, we estimate consumer spending on The Big Game will result in 8.6 million tonnes of CO2e.

8.6 million tonnes of CO2e. That’s a lot. In context, that's more CO2e emissions than Costa Rica produces in a year (8.28 million tCO2e)! 

And that 8.6m only covers consumer spending... imagine how many more emissions are created by the event itself. All those private jets taking celebrities to the game, the energy consumed by the stadium, putting players up in hotels etc.

How did Lune calculate this using emissions intelligence?

To calculate the emissions generated by consumer spending on Sunday’s game we used spend-based data from the National Retail Association survey. By breaking down the total spent ($18.6bn) into categories, we populated a .CSV file. 

(Alternatively, we could have used Lune’s API integration.)

This file was then uploaded into Lune’s emission intelligence engine. The intelligence instantly matched the categories with the most appropriate emission factor. To make the results more accurate, US emission factors were automatically selected. The output is spend-based emission calculations.

How accurate are spend-based emission calculations? 

Spend-based emission calculations make emissions reporting accessible. Every business has to track its finances, which means every business can track its emissions. 

It’s one of the four methods outlined by the GHG Protocol, the leading international standard for carbon accounting. Climate disclosures, like the EU CSRD, recommends companies use the GHG Protocol to calculate their emissions. Therefore, this method can support compliance. 

Learn more: What is the best method for calculating emissions?

While the spend-based method acts as an excellent starting point for calculating emissions, it lacks accuracy. For example, if Nike had a sale and reduced the price of their American Football shoes by 50%, the spend-based emission estimates would also fall by 50%. But the actual emissions produced would remain the same, regardless of the price change. 

For reporting, spend-based emission estimates are widely accepted. They’re great for pinpointing emission hotspots. Companies can then drill down into these hotspots by enhancing the granularity of spend-based calculations, or use activity-based or supplier-based calculations.

Enrich your spend data with emission intelligence

While Lune’s emission intelligence could not predict the outcome of the Eagles vs. Chiefs game, it can make emissions visible. We can only manage what we can measure. And managing emissions is a global imperative.

This is why leading spend management platforms, such as Payhawk, Soldo, and Simfoni, are enriching their spend data with emission intelligence. This means their end-users have real-time visibility into their emissions, save time on climate compliance with automatically generated reports, and can start pinpointing hotspots ripe for decarbonisation. 

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*Calculations made with NRF spend data