T. Fürmann, M. Schäfer, N. Harder, R. L. Grether, R. Qussous, and A. Weidlich, "Generation-based and consumption-based grid emission intensity time series for German federal states 01/2020 - 07/2024 [Data set]", Zenodo, 2024.
The dataset contains time series estimating the consumption mix, generation-based, and consumption-based grid emission intensity of German federal states for the period January 2020 to end of June 2024, as shown on the CO₂Map website. For an explanation of the underlying methodology, see the CO₂Map Methodology section. A detailed scientific article is currently in preparation.
M. Schäfer, T. Fürmann and A. Weidlich, "CO2Map.de release webinar slides", Freiburg im Breisgau, Germany, 2024
In this webinar, we present the CO₂Map.de platform and its features. We show how to use the platform to explore the CO₂ emissions of different countries and regions, and how to access the data via the API. We also present the methodology behind the data and the platform, and discuss the potential applications of the data.
M. Sundblad, T. Fürmann, A. Weidlich and M. Schäfer, "Load and generation time series for German federal states: Static vs. dynamic regionalization factors" 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES), Aachen, Germany, 2023, pp. 1-6, doi: 10.1109/OSMSES58477.2023.10089686.
Electricity generation and demand time series often are only available on a national scale. In this contribution, we derive regionalization factors to allocate publicly available national generation and demand time series for Germany to the federal-state level. We compare two different types of regionalization approaches: Static factors are based on the regional distribution of capacities or population and GPD, whereas dynamic factors take plant-specific generation time series, regionally resolved weather patterns or compositions of different load profiles into account. We observe that dynamic regionalization factors show significant temporal variability, emphasizing the limitations of static regionalization factors for a spatio-temporally more detailed representation of power system time series.
M. Schäfer, B. Tranberg, D. Jones and A. Weidlich, "Tracing carbon dioxide emissions in the European electricity markets," 2020 17th International Conference on the European Energy Market (EEM), Stockholm, Sweden, 2020, pp. 1-6, doi: 10.1109/EEM49802.2020.9221928.
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.