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 3821–3840 of 14385 papers

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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🌍 GlobalPreprintSSRN#Disclosure Infrastructure

Climate disclosure in a world of political risk

(著者不明)

This paper examines how political risk affects corporate climate disclosure, focusing on the impact of policy uncertainty on disclosure quality and quantity, offering implications for firms and regulators.

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🌍 GlobalPreprintSSRN#Transition Finance

The Global Green Finance Index 12

(著者不明)

The 12th edition of the index evaluating and ranking the quality of green finance in global financial centers, providing investors and policymakers with a benchmark of green finance maturity.

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🌍 GlobalPreprintZenodo2026#EV & TransportDOI

ELECTRIC VEHICLES: DEVELOPMENT AND EVOLUTION

Azizov Shavkat Abdurakhmanovich Professor, Karshi State Technical University

This article examines the historical development and technological evolution of electric vehicles (EVs) from early experiments in the 19th century to modern advanced systems. It analyzes key technological milestones, economic factors, and e…

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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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