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.
Showing 3261–3280 of 26757 papers
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Using 124 firm-year observations from 31 Indonesian financial companies, this study finds that board size influences ESG disclosure. Effective audit committee oversight moderates this relationship, encouraging more extensive and higher-qual…
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This study compares manual content analysis with AI-assisted semantic evaluation of sustainability disclosure at Saudi Arabia's four fully Shariah-compliant banks (2022–2024), using a hybrid ESG–Shariah framework across five dimensions. Dis…
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Using textual analysis of 10-K filings from US listed firms (2009-2019), this study examines how firm life-cycle stages shape sustainability disclosure. Mature firms disclose more, consistent with signaling theory, while growth-stage firms …
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Using Ghana's Parliament House as a case study, this paper assesses the technical and economic feasibility of rooftop/carport solar PV-grid integration and green hydrogen/ammonia production via GIS and Python simulation. A 6.3 MW solar syst…
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This roadmap integrates fluid dynamics, combustion chemistry, advanced diagnostics, and machine learning to enable the low-carbon transition. It highlights hydrogen, ammonia, and sustainable aviation fuels as key energy carriers, alongside …
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Using a multi-source dataset linking Chinese A-share firms, cities, and local government work reports (2007–2022), this study shows that greater local environmental attention reduces corporate carbon emissions by 0.956% per standard deviati…
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The paper links the assets of the top 500 billionaires to emissions, building an ownership-based carbon accounting dataset. Each million USD held is tied to over 65 tCO2e per year, about 10x the average person's footprint, with emissions fa…
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This paper proposes an electricity–thermal–hydrogen–gas integrated energy system coupling oxy-fuel combustion capture (OCC), coal-to-hydrogen (C2H), and power-to-gas (P2G). A multi-source hydrogen supply and ladder-type carbon trading with …
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This paper proposes a hybrid deep-learning model combining TCN and FEDformer to forecast carbon emission allowance trading prices. Improved price prediction matters for compliance cost planning and investment decisions in emissions trading …
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This paper proposes a three-stage carbon trading price prediction model combining time–frequency decomposition with a hybrid attention mechanism. Tested on Guangdong and Hubei data, it reduces single-step MAE by 1.1–12.9% and MSE by 10.5–13…
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Using panel data of Chinese listed firms (2010–2024) and a multi-period DID model, this study finds that the carbon emissions trading system significantly raises firm total factor productivity. Baseline-based accounting, paid quota allocati…
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A meta-analysis synthesizing evidence on how combining carbon pricing with renewable-energy support policies affects emission reductions and welfare. It systematically assesses policy interactions, overlaps, and synergies across studies. Fi…
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This article analyzes how China localized the global carbon market norm, particularly the EU ETS, into its domestic climate governance using constructivist IR theory and Acharya's norm localization framework. Rather than replicating the Eur…
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This PRISMA-based review synthesizes literature on Industry 5.0, the 10R circular framework, ESG mandates, and deep decarbonization technologies. It argues that while digital twins and AI optimize energy efficiency, long-term net-zero requi…
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This study presents a hybrid physics-informed machine learning pipeline for NO2 dispersion and short-term forecasting along a high-traffic corridor in Palermo, Italy, using six years of hourly data. Combining COPERT emissions, the SIRANE st…
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This review synthesizes literature on sustainable supply chain management (SSCM), identifying four perspectives—environmental, social, economic, and governance. Key challenges include paradoxical tensions between sustainability and efficien…
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The FairTravel program has worked with India's IT industry since 2021 to cut corporate flying, a major Scope 3 emissions source. Using social-practice theory, it shifts mindset, behavior, and policy together, engaging EU clients on shared S…
Taize Yu, Mingxuan Lyu, Ruiling Qu +5
Using an extended STIRPAT model with ridge regression, this study analyzes determinants of EU-27 energy-related carbon emissions (1996–2023), incorporating geopolitical risk and energy transition. Four scenarios show GDP and unemployment po…
Ziqi Zhao, Mingming Jia, Luhe Wan +6
First global-scale assessment of how edge effects in fragmented Ramsar-protected mangroves bias blue carbon estimates. Edge penetration is under 100 m in ~63% of forests, where biomass drops 5.15% on average. Ignoring edges overestimates ca…
Emily A. Ury, Zhen Zhang, Etienne Fluet‐Chouinard +3
Restoring 30% of the world's drained inland peatlands strategically could sequester 0.91±0.17 Pg CO2eq/yr, three times more than random restoration. Prioritizing water quality or flood mitigation still yields 0.34–0.50 Pg CO2eq/yr, showing …
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