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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Showing 32661–32680 of 36620 papers

Peer-reviewed🇪🇺 EuropeJournalEnergies2026#Energy TransitionDOI

Biogas in The Netherlands: Hesitant Adoption on Many Levels

Gideon A.H. Laugs, Henny van der Windt

This paper analyzes barriers to biogas adoption in the Netherlands using the Technological Innovation Systems (TIS) framework, focusing on local energy initiatives (LEIs). It identifies insufficient financial and knowledge resources, and la…

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Peer-reviewedJournalZenodo (CERN European Organization for Nuclear Research)2026#Energy TransitionDOI

VISUALIZATION OF ENERGY WITH ZERO CARBON FOOTPRINT USING VOSVIEWER

GELMANOVA ZOYA SALIKHOVNA, FAYEZ WAZANI ABDUL WALID

This study uses VOSviewer to perform a bibliometric analysis of 19,450 publications from 2020-2025, visualizing the structure of zero-carbon energy research. It identifies key themes like renewable energy, energy transition, and AI integrat…

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Peer-reviewed🌍 GlobalJournalFrontiers in Environmental Science2026#ESGDOI

Climate policy synergy: a tripartite evolutionary game analysis of ESG compliance and tax incentives on corporate carbon governance

Zhisheng Qin, Ying-Jun Lin, Shaojun Liu

This paper uses a tripartite evolutionary game model to analyze how tax incentives affect corporate carbon emission reduction under ESG compliance management. By integrating ISO 37301 compliance frameworks and OECD carbon pricing benchmarks…

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Peer-reviewedCNJournalChina Agricultural Economic Review2026#Carbon PricingDOI

Co-benefits and trade-offs of carbon revenue recycling schemes on China's water, energy and food systems under carbon neutrality target

Xiangyan Qian, Hongdian Jiang, Yun-Fei Yao +4

This study analyzes four carbon revenue recycling schemes in China's carbon neutrality path using a dynamic CGE model. Lump-sum transfers to households improve welfare and reduce urban-rural income gaps, while indirect tax cuts minimize GDP…

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Peer-reviewed🌍 GlobalJournalEnergy Sustainable Development/Energy for sustainable development2026#Energy TransitionDOI

System dynamics model for sustainable energy transition in the Republic of Benin

Maris Esdras Tokpassi, Abdellah Benyoucef, Babajide Epe Shari +4

This paper proposes a system dynamics model to simulate sustainable energy transition in Benin, integrating renewable energy deployment, policy interventions, and economic impacts. It provides long-term pathways and insights for policymaker…

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Peer-reviewedCNJournalMitigation and Adaptation Strategies for Global Change2026#Carbon PricingDOI

Municipal carbon allocation in China’s provincial budget system: integrating equity, efficiency, and regional preferences

Lianbiao Cui, Guofeng Song, Mei Duan

This paper proposes a method for allocating carbon emissions to municipalities within China's provincial budget system. It integrates equity, efficiency, and regional preferences, offering insights for carbon budget management policy in Chi…

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Peer-reviewed🌍 GlobalJournalRecent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering)2026#Energy TransitionDOI

Deep Reinforcement Learning-Based Multi-Objective Coupling Optimization of Economy, Low-Carbon and Energy Efficiency for Integrated Energy Systems

Hongyin Chen, Songcen Wang, Xiaoqiang Jia +5

This paper proposes a multi-objective coupling optimization strategy for integrated energy systems (IES) targeting economy, low-carbon, and exergy efficiency using deep reinforcement learning. It incorporates demand response models for elec…

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