Tracing carbon dioxide emissions in the European electricity markets

TL;DR

This paper tackles the attribution of electricity-related emissions in the European grid by propagating power flows through a flow-tracing framework. It employs a multi-regional input-output approach and compares two coupling variants—direct coupling and aggregated coupling—to compute consumption-based emission intensities $e_m^{\mathcal{C}} = \frac{\sum_{\alpha,n} e_{(n,\alpha)} d_{m,(n,\alpha)}}{d_m}$. Using hourly ENTSO-E data for 30 countries from 2016–2019 and emission factors from Tranberg2019, it shows that methodological choices can substantially alter emission characterizations, particularly for smaller, well-connected countries. The work emphasizes the importance of transparent, data-rich, and reproducible methodologies for emission accounting in highly interconnected energy systems.

Abstract

Consumption-based carbon emission measures aim to account for emissions associated with power transmission from distant regions, as opposed to measures which only consider local power generation. Outlining key differences between two different methodological variants of this approach, we report results on consumption-based emission intensities of power generation for European countries from 2016 to 2019. We find that in particular for well connected smaller countries, the consideration of imports has a significant impact on the attributed emissions. For these countries, implicit methodological choices in the input-output model are reflected in both hourly and average yearly emission measures.

Figures (5)

• Figure 1: Transmission network model with 30 ENTSO-E member countries as nodes, and 57 interconnectors as links. Arrows indicate average hourly cross-border physical flows in 2019 according to data from the ENTSO-E Transparency Page transparency. The largest flows occur from Switzerland to Italy (2.4 GW), from Sweden to Finland (1.8 GW), and from France to Germany (1.5 GW).
• Figure 2: Top: Mix of total generation for the years 2016 to 2019 aggregated over 30 ENTSO-E member countries. Bottom: Total generation-based emissions for the years 2016 to 2019. Dark grey values show the aggregates over internal generation (that is, excluding net exports), light grey represents aggregates over external generation (that is, net imports only).
• Figure 3: Evolution of the total external generation mix (top) and associated emissions (bottom) from 2016 to 2019.
• Figure 4: Consumption-based emission intensities in gCO$_2$eq/kWh based on the direct (x-axis) and the aggregated (y-axis) coupling scheme. Each dot corresponds to one hour in 2019. The distribution of these intensities over the year is visualised in the margins, respectively. Top left: Germany. Top right: Denmark. Bottom left: France. Bottom right: Austria.
• Figure 5: Average generation- and consumption-based emission intensities for 30 ENTSO-E member countries in 2019, in comparison to their local share of non-fossil power generation. Green: generation-based. Blue: consumption-based, direct coupling scheme. Orange: generation-based, aggregated coupling scheme. Figure adapted from Tranberg2019.