The Impact of the Russian War against Ukraine on the German Hydrogen Discourse

Martha Loewe, Christine Quittkat (), Michèle Knodt and Ingrid Ott
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Martha Loewe: KIT Campus Süd, Karlsruhe Institute of Technology (KIT), Geb. 01.87-5. OG, Rüppurrer Str. 1a, Haus B, 76137 Karlsruhe, Germany
Christine Quittkat: Institute for Political Science, Technical University Darmstadt, Residenzschloss 1, 64283 Darmstadt, Germany
Michèle Knodt: Institute for Political Science, Technical University Darmstadt, Residenzschloss 1, 64283 Darmstadt, Germany
Ingrid Ott: KIT Campus Süd, Karlsruhe Institute of Technology (KIT), Geb. 01.87-5. OG, Rüppurrer Str. 1a, Haus B, 76137 Karlsruhe, Germany

Sustainability, 2024, vol. 16, issue 2, 1-21

Abstract: This contribution delves into the transformative effects of the Russian–Ukrainian war on the discourse surrounding German hydrogen. Employing structural topical modeling (STM) on a vast dataset of 2192 newspaper articles spanning from 2019 to 2022, it aims to uncover thematic shifts attributed to the Russian invasion of Ukraine. The onset of the war in February 2022 triggered a significant pivot in the discourse, shifting it from sustainability and climate-change mitigation to the securing of energy supplies through new partnerships, particularly in response to Russia’s unreliability. Germany started exploring alternative energy trading partners like Canada and Australia, emphasizing green hydrogen development. The study illustrates how external shocks can expedite the uptake of new technologies. The adoption of the “H2 readiness” concept for LNG terminals contributes to the successful implementation of green hydrogen. In summary, the Russian–Ukrainian war profoundly impacted the German hydrogen discourse, shifting the focus from sustainability to energy supply security, underscoring the interconnectedness of energy security and sustainability in Germany’s hydrogen policy.

Keywords: hydrogen; discourse; green energy trade; Germany; Ukraine; STM; structural topic model; text as data; unsupervised machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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