gxceed
GX Research Hub · English

GX & Decarbonization Research

This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open 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 3861–3880 of 13090 papers

🌍 Global📚 Peer-reviewed · JournalJournal of Environmental Economics and Sustainability2026#climate_smart_agricultureDOI

Integrating Climate-Smart Strategies into Farming Systems: Implications for Sustainability and Resilience

Moseb Mamasao, Aldrees Ansary Guro, Rasmiah Mama

This systematic literature review of 38 articles (2013-2026) evaluates integrated climate-smart agriculture (CSA) strategies. Bundling sustainable intensification, conservation agriculture, agroforestry, and water management enhances soil c…

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🇪🇺 Europe📚 Peer-reviewed · JournalLatvian Journal of Physics and Technical Sciences2026#Renewable EnergyDOI

Myths and Participation Gaps of Renewable Energy Project Resistance in Latvia

L. Zemite, L. Jansons, D. Kronkalns +3

This mixed-methods study investigates local resistance to renewable energy projects in Latvia, finding that opposition stems from low institutional trust, weak procedural justice, and misinformation rather than climate goal rejection. Struc…

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PreprintSSRN#Carbon Accounting

Multi-Counting in Scope 1, 2, and 3 Upstream Emissions

(著者不明)

This paper analyzes multi-counting issues in GHG emission accounting across Scopes 1, 2, and 3 upstream emissions. It highlights how double counting undermines the reliability of corporate emission reports and reduction targets, emphasizing…

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PreprintZenodo2026#AI × ESGDOI

AI-FORECASTED TECHNO-ECONOMIC AND ENVIRONMENTAL ASSESSMENT OF BIOGAS, METHANE (CH₄), HYDROGEN (H₂), AND ELECTRICAL POWER GENERATION AT A DAIRY FARM IN AL-DHLAIL, ZARQA, JORDAN

Habes Ali Khawaldeh, Moath Bani Fayyad, Mohammad Al-Smairan, Wasseem Al Rousan and Omar Alnhoud

This paper designs a fixed-dome biogas plant for a 200-cow dairy farm in Jordan, performing techno-economic and environmental assessment with LSTM-based AI forecasting. Results show a 4-year payback, LCOE ~0.093 USD/kWh, and 28.46 tCO2/year…

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