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.
Showing 8061–8080 of 16539 papers
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This paper empirically examines the impact of carbon tax on green innovation (e.g., patent filings) in EU countries. It finds that carbon taxes stimulate corporate R&D investment and increase environmental technology patents. The study empl…
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This paper analyzes the impact of carbon tax on economic growth and environmental quality. Carbon taxes are effective for GHG reduction but may have negative economic consequences.
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This paper focuses on data quality issues in Scope 3 emissions and proposes machine learning prediction methods. It aims to improve accuracy in estimating supply chain-wide emissions.
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This paper proposes a framework linking supply chain finance with carbon accounting data, enabling companies to incorporate emission data into financial terms and incentivize decarbonization across the supply chain. While specific methods a…
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This paper empirically examines the impact of climate change disclosure on firms' cost of capital, finding that higher-quality disclosure is associated with lower cost of capital, highlighting investor valuation of transparency.
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This paper empirically analyzes the factors driving firms' adoption of TCFD recommendations and the performance effects of such adoption, providing insights into the determinants and financial impacts of climate disclosure.
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This paper empirically examines whether green finance drives firms to translate ESG talk into concrete action. It investigates the effectiveness of green finance in promoting genuine corporate ESG practices and identifies conditions under w…
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This paper argues that China's proposed new climate disclosure framework represents a 'third way' distinct from existing TCFD/ISSB standards. Combining policy-driven and market-based mechanisms, China's approach could influence the diversit…
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This paper proposes a machine learning approach to predict ESG ratings. It builds models that estimate ESG scores from publicly available corporate data and compares performance with traditional methods. The research contributes to automati…
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This paper examines the framework for non-financial reporting on climate risks and opportunities, aligning with global disclosure standards such as TCFD and ISSB. It discusses improving report quality and usefulness for investor decision-ma…
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This paper proposes a dual-purpose accounting framework for the net-zero transition, integrating financial and carbon accounting to enable consistent reporting of emission reductions and financial performance. It aims to enhance transition …
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This study proposes and validates a machine learning-based approach to analyze corporate climate disclosures, highlighting the use of AI for assessing disclosure quality and compliance.
Qorriyeva Shahnoza Safarbayevna
This paper analyzes green project financing in Uzbekistan. From 2020-2024, renewable capacity grew to ~5,434 MW, SDG bonds of USD 235M and a sovereign green Eurobond of USD 350M were issued. However, regulatory, capital market, and transmis…
Adel Elgammal
This study proposes a hybrid floating offshore wind-solar platform and validates its design using an AI optimization framework combining machine learning, deep reinforcement learning, and genetic algorithms. Results show 32% higher energy o…
Xu S.
This paper comprehensively reviews challenges and emerging trends in hydrogen energy industrialization. It covers the entire process from hydrogen evolution reaction to storage, transportation, and utilization, discussing technical barriers…
Zhang Y.
This paper proposes methods to apply artificial intelligence to optimize the operation of thermal power plants, thereby reducing carbon dioxide emissions. By utilizing AI, it is possible to improve combustion efficiency and reduce downtime …
Goudar P.S.
This paper proposes the electrolysis of cow urine as a method for producing green hydrogen, integrating waste treatment with energy generation. The approach aligns with circular economy principles by converting a waste product into a valuab…
Ma Z.
This paper presents a case analysis of CO2 leakage monitoring point deployment methods in CCUS projects, offering practical recommendations for effective monitoring.
Nguyen Q.M.
This paper proposes a multi-objective optimization method for subsurface CO2 capture, utilization, and storage (CCUS). It applies sequential quadratic programming with stochastic gradients to evaluate trade-offs between economic and environ…
Orujov A.
This review covers CCUS technologies focusing on foam-based methods for enhanced CO2 storage, regulatory frameworks, and monitoring techniques. It highlights the potential of foams to improve storage efficiency and the need for robust regul…
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