Finding and selecting the correct emission factor can be a challenging part of carbon footprint calculation. The question arises how to choose the right emission factor and what impact it has on the calculation results. Can a spend-based calculation based on a company’s purchasing data provide reliable results?
Earlier this year, we wrote a blog about how to select the correct emission factor and how it can effect emission calculations. The blog explored the reliability of emission factors and the impacts of using euro-based compared to physical unit-based emission factors.
The need for diverse emission factors will grow significantly in the coming years. Scope 3 calculations will become relevant for companies that fall under the Corporate Sustainability Reporting Directive (CSRD). These requirements may also broadly impact subcontractors, for example. Using currency-based emission factors might be tempting because of its simplicity. For example, just by checking the company’s accounts you can determine the cost of raw material purchases during the reporting year and find the emission factor corresponding to the product category. However, it is important to note that such calculations typically result in significantly higher emissions compared to calculations based on physical quantities. Therefore the accuracy of the final results may suffer.
Emission calculations should always be based on widely accepted standards that set requirements for the calculations. The CSRD requirements and OpenCO2net tools are based on the GHG Protocol standards. The standards recommend using spend-based data as a last resort only when no other method can be applied. Before using spend-based data, either supplier-specific or average data based on physical quantities should be used. The availability of emission factors is continually improving, so there is no reason to rely solely on euro-based calculations.
The impact of emission factors on the carbon footprint
The inaccuracy of euro-based emission factors increases the uncertainty of calculations. For instance, they do not take into account the differences between countries, companies, production methods or products. Instead they significantly average out emissions. Two companies producing the same product can have substantial differences in emissions at both the company and product levels. These differences may arise from factors such as the energy used, production equipment, and raw materials. When relying solely on euro-based input data, these differences are not captured, nor can the benefits of using recycled raw materials be demonstrated.
Let’s compare the emissions from pulp production as an example. In Finland, pulp production emissions are relatively low on average, as the energy used in production typically comes from renewable bioenergy generated during the process. If 1 ton of pulp is produced and the emissions are calculated based on this mass, the emissions would be approximately 300 kg CO2e. However, if pulp is purchased for 1,500 euros and emissions are calculated using a currency-based emission factor, the emissions would be around 970 kg CO2e. The difference between these two calculation methods is more than threefold.
If we compare the emissions caused by the production of Apple’s iPhone to price data, the difference between them is significant. The figure below presents the emissions calculated and published by Apple for the latest iPhone 16 model. For comparison, the emissions based on the price of the same model are shown next to it. At the time of writing, the iPhone 16 costs 999 euros, and as can be seen, the difference between the physical and euro-based calculations is substantial.
Spend-based data affects the calculated size of the carbon footprint
Emission factors based on currency data do not account for price changes or factors like inflation, which has been relatively high in recent years. Euro-based emission calculations only reflect the increased price. This means that emissions would appear higher, even if no changes in the production process have occurred. Let’s look at this with the emissions data for rainbow trout, as the price of it increased significantly with rising inflation. On average, rainbow trout farmed in Finland produces about 5.4 kg CO2e per kilogram of fish. If the price of rainbow trout is on sale for 9.9 €/kg, the emissions calculated using euro-based data would be about 6.5 kg CO2e per kg. Where as at a price of 17.99 €/kg, the emissions would rise to nearly 11.8 kg CO2e per kg. These differences are illustrated in the following figure.
The impact of price is also evident in products made from recycled materials. For example, consider a company that wants to reduce its product’s emissions. It does this by choosing recycled steel as a raw material instead of virgin steel with significantly higher emissions. However, recycled steel may be more expensive, and if the emissions of these two raw materials are compared solely based on the euros spent, recycled steel would appear to have higher emissions, even though the reality is entirely the opposite.
In addition to the differences outlined above, spend-based data also requires consideration of currency conversions. Not all emissions data is based on euros, necessitating currency conversions using average exchange rates, which increases uncertainty in the use of currency-based emission factors. Furthermore, there may be other price uncertainties: for instance, whether the price is directed at the end consumer (i.e., whether it includes the seller’s margin, for example) or whether the price information includes value-added tax (VAT).
Reliable emission calculations help achieve real emission reductions
As mentioned at the beginning, emission calculations based on consumption data may seem straightforward, but the results can be surprising. If emissions have previously been calculated with physical quantities based data, calculations based on consumption data introduce substantial uncertainties and likely result in up to twice as high emissions.
In some cases, using currency-based input data and emission factors in calculations is justified and has its place. For example, emissions from services purchased by a company are typically calculated using spend-based data. This is because there is currently no practical alternative for considering services such as insurance or occupational healthcare. Most importantly significant emission sources related to a company’s operations, such as raw material and chemical procurement, should ideally be addressed in the calculations using physical quantities based data.
The more accurate the input data used in calculations, the more precise the final result will be. Highly accurate emission calculations help identify and implement real emission reduction measures and demonstrate that a company’s emissions are decreasing in line with its targets. Suppose the goal is to conduct calculations, for example, in accordance with the CSRD and follow GHG Protocol standards. In that case, priority should be given to obtaining supplier-specific, detailed input data and emission factors.
The OpenCO2net emissions database is compiled by emission calculation experts and already contains around 8,000 up-to-date emission factors. In addition to emission factors from public sources, the database also includes supplier-specific emission factors, for example, from SSAB and UPM. With the OpenCO2.api interface solution, emission factors can be integrated into companies’ own systems. Furthermore, the OpenCO2net platform offers standard-based carbon footprint calculators for both organizational and product carbon footprint calculations.
