GX Research Hub · English

GX & Decarbonization Research

This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.

The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.

Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.

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Topic: #Carbon Pricing (clear)

Showing 2181–2200 of 2209 papers

Peer-reviewedJournalFachrepositorium Lebenswissenschaften2026#Carbon PricingDOI

Carbon pricing and the affordability of residential heating

Milan Jakob Reda, Erik Gawel, Paul Lehmann +1

This paper examines the impact of carbon pricing on residential heating costs, highlighting regressive effects on low-income households and the need for complementary policies. It proposes measures to enhance social acceptability based on e…

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Peer-reviewed🇪🇺 EuropeJournalZenodo (CERN European Organization for Nuclear Research)2026#Carbon PricingDOI

To make European climate policy work, we need to put a carbon price on imports

Emil Dimanchev

This paper argues that for European climate policy to be effective, a carbon price on imports is essential. It emphasizes the importance of border carbon adjustments like CBAM to prevent carbon leakage and maintain competitiveness. It exami…

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Peer-reviewed🌍 GlobalJournalInternational Journal of Theoretical and Applied Finance2026#Carbon PricingDOI

EMISSION IMPOSSIBLE: BALANCING ENVIRONMENTAL CONCERNS AND ENERGY PRICES

Rene Aid, Maria Arduca, Sara Biagini +1

This paper develops a theoretical framework to analyze how carbon pricing policies affect domestic energy producer prices and quantify the policy-driven price impacts of achieving net-zero emissions. It models energy firms' behavior under e…

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Preprint🇪🇺 EuropeApplied Energy2026#Carbon PricingDOI

Uncovering drivers of EU carbon futures with Bayesian networks

Maciejowski, Jan, Leonelli, Manuele

This paper uses Bayesian networks to analyze drivers of EUA futures prices under the EU ETS, covering 2013-2025. Energy commodities (coal, oil) are the most influential, while stock market sentiment affects prices indirectly. The dynamic mo…

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