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 1941–1960 of 4241 papers

Peer-reviewed🌍 GlobalJournalZenodo (CERN European Organization for Nuclear Research)2026#Climate FinanceDOI

Blockchain Technology in Climate Finance and Carbon Markets: Emerging Infrastructure, Market Dynamics, and the Road to Net Zero

Anson Joseph

This paper analyzes blockchain and DLT's role in climate finance and carbon markets, drawing on 26 peer-reviewed studies and market intelligence. It synthesizes 2025-2026 developments in ReFi, Web3, and Layer 2 architectures, introduces a B…

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Peer-reviewedCNJournalElectronics2026#Energy TransitionDOI

Impact Assessment of a Dynamic Green Certificate and Green Hydrogen Certificate Joint Mechanism on Integrated Energy Systems Based on an Asymmetric Cloud Matter-Element Model

Hao Li, Jiahui Wu, Weiqing Wang

This study proposes a dynamic green certificate (GCT) and green hydrogen certificate (GHCT) joint mechanism to enhance wind power integration and reduce carbon emissions in integrated energy systems (IES). An optimal operation model conside…

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Peer-reviewed🌍 GlobalConferenceSPE Conference at Oman Petroleum & Energy Show2026#Energy TransitionDOI

Optimized Reduced-Portland Cement System for Lowering Carbon Emissions in Well Cementing Operations

Nazia Bhimani, Zahra Al Sulaimi, Dua Al Shibani +1

This paper presents the design, lab evaluation, and field implementation of a reduced-Portland cement system for well cementing, substituting 37% of Portland cement with SCMs. In a large-scale drilling project in Oman, this achieved ~130 to…

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Preprint🇺🇸 USAZenodo2026#AI × ESGDOI

INTEGRATING GREEN ECONOMY AND FINANCIAL TECHNOLOGIES TO ADVANCE ENVIRONMENTAL SUSTAINABILITY

Sonia Sayari, Nidhal Mgadmi, Majed A Helmi, Hanen Louati, Abdulaziz M Basahel, Hamed Yousef Alshinkity, Sumayya Albalawi

Using US data from 1990-2024, this study examines how green economy, FinTech, and governance affect environmental sustainability. Applying cointegration, error-correction, QVAR, and heatmap diagnostics, it finds that renewable energy, fores…

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Preprint🇺🇸 USAZenodo2026#Energy TransitionDOI

Regional Energy Deployment System Model 2.0 (ReEDS 2.0)

Brown, Patrick, Carag, Vincent, Chen, Yunzhi +19

ReEDS 2.0 is a capacity planning model simulating the evolution of the U.S. bulk power system through 2050. It is widely used for analyzing renewable deployment and decarbonization pathways, providing critical insights for policy and indust…

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Peer-reviewed🇪🇺 EuropeJournalInternational Journal of Hydrogen Energy2026#HydrogenDOI

Dynamic optimisation of alkaline electrolyser operation under virtual solar and hybrid solar-wind PPAs – A multi-state MINLP framework applied to the TRIERES hydrogen valley project

Nikolaos Skordoulias, Sotiriοs Karellas, Dimitrios V. Lyridis +2

This study proposes an integrated optimization framework for dynamic operation of pressurized alkaline electrolysers powered by hybrid solar-wind PPAs. A multi-state module-level model with MINLP constraints minimizes operating costs. Appli…

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Peer-reviewed🇨🇳 ChinaJournalRemote Sensing2026#AI × ESGDOI

Precision Estimation of Aboveground Carbon Stock in Acidosasa edulis Bamboo Forests: A Fusion Approach with UAV-LiDAR, Allometric Equations, and Machine Learning

Xiaoyu Guo, Weisen Wang, Zhanghua Xu +6

This study develops a UAV-LiDAR and machine learning framework for organ-level aboveground carbon (AGC) estimation in bamboo forests. XGBoost and Random Forest achieved highest accuracy (stem R2=0.82, leaf R2=0.73), offering a cost-effectiv…

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Peer-reviewed🌍 GlobalJournalChemistry2026#CCUSDOI

Commercial-Scale Demonstration of Carbon Capture and Utilisation (CCU) from a Nickel Refinery Off-Gas Using Microalgae in a Closed Vertical Tube Photobioreactor

Emily Preedy, Darren L. Oatley-Radcliffe, Jose Gayo Pelaez +3

This study demonstrates a commercial-scale tubular photobioreactor using CO2 from a nickel refinery to grow microalgae, achieving biomass productivity of 0.11 g/L/d and sequestering ~1 tonne CO2/year. Techno-economic analysis shows positive…

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