Transaction to Carbon
Methodology to estimating Carbon Intensity Factors
Carbon intensity is the amount of carbon dioxide (CO2) emissions released per unit of another variable, such as gross domestic product (GDP), output energy use, or transport (Allwood et al., 2014).
In the Open standard framework for consumer carbon calculations based on payment transactions, emission intensity is measured in grams of CO2e emitted per monetary unit spent in a specific activity and country, which is the emission rate of a given pollutant relative to the intensity of a specific activity or an industrial production process (Du et al., 2018). The concept has been mostly used for energy analysis, for example, grams of carbon dioxide equivalent released per megajoule of energy produced (Ali et al., 2022; Cheng et al., 2018; Hocaoglu & Karanfil, 2011; Zhu et al., 2014), or the ratio of greenhouse gas emissions produced to gross domestic product (Davis & Caldeira, 2010; Garrone & Grilli, 2010; Hocaoglu & Karanfil, 2011). In the Open Standard, carbon intensity estimations are derived from a carbon footprint and expenditures per household consumption categories.
Approach for estimating carbon intensity
The combination of second-level personal spending data and carbon values per category gives dedicated values for the given categories that are country specific. This country-specific approach reflects and considers the prevalent significant variance regarding expenditures and emissions, which particularly apply to certain consumption categories, e.g., ‘groceries,’ where the locality of consumption considerably affects the carbon footprint.
Carbon footprint calculations are derived from secondary data from scientific publications and official technical documents generated by research centres, universities, national accounting systems, and regional platforms.
There are two approaches to deriving carbon intensity factors based on data availability: ecolytiq 1.4 and EEIO-Hybrid. Both apply the household consumption model based on functional units and expenditures, but the level of disaggregated data varies between the two approaches, as explained below. Different use cases and goals help determine which of these approaches should be adopted by an organization. Figure 1 shows the decision tree the user should apply when deciding what approach to follow.
Here we present the ecolytiq 1.4 approach, which should be applied when country-specific data is unavailable in the EXIOBASE 3 (Stadler et al., 2019) or the COICOP databases (D. B. Eurostat, 2022).
When country-specific information is available in the EXIOBASE 3 and COICOP datasets, we apply the EEIO-Hybrid methodology.