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 21–40 of 1384 papers
Freda, Wu
This working paper evaluates the commercial viability of industrial CCUS projects under the US 45Q tax credit structure using discounted cash flow analysis. It compares the impact of the phased credit on net present value across sectors and…
Yuhao Huang, Novarun Deb, Hamidreza Zareipour
This paper analyzes the sustainability implications of rapidly growing AI data center electricity demand on power systems. It evaluates both short-run operational and long-run planning mechanisms, assessing risks of increased emissions and …
(著者不明)
This paper critically examines the role of export credit agencies (ECAs) in the energy transition. It discusses how ECAs often finance fossil fuel projects but could also support clean energy transition, questioning whether they contribute …
(著者不明)
This paper presents a method to link global integrated assessment models with hybrid input-output models to evaluate decarbonization policies for the steel sector. Focusing on Europe, it analyzes the impacts of policy scenarios, aiming to b…
(著者不明)
This paper compiles blue carbon inventories for Spain and Portugal, quantifying carbon stocks and sequestration rates in coastal ecosystems such as seagrasses and salt marshes. It discusses methodologies for integrating these natural carbon…
(著者不明)
This paper argues that existing forest carbon protocols fail to adequately account for the increased risk of carbon loss due to climate change, potentially overstating the climate benefits of forest carbon projects.
Xuandong Zhang, Yankui Su, Jinjiang Li +1
This study proposes a method using digital trace data (mobile phone signals, POI check-ins, traffic data, etc.) to predict low-carbon urbanization. A hybrid model combining spatiotemporal graph convolutional network and LSTM identifies carb…
Subhodeep Mukherjee, Ruchi Sharma, Rashmiranjan Panigrahi +1
This systematic review examines how digital technologies (IoT, blockchain, AI, big data) enhance circular supply chain (CSC) performance. Four themes emerge: use of digital tech to optimize CSC processes, key industries (manufacturing, elec…
Jasmine Selvakumari Jeya Israel, Aldrin Joan Pandian William, Pradeep Kumar Mishra +1
This study proposes a Bi-LSTM-based approach to optimize emission forecasting, carbon offset allocation, and green fund utilization for steel, cement, and aluminum industries. Bi-LSTM demonstrates superior performance in long-term predictio…
Bo Liu, Yi Ding, Haoying Guo
This paper analyzes a manufacturer's optimal choice between direct carbon reduction investment (R strategy) and carbon offset (O strategy) under demand uncertainty and information asymmetry using a game-theoretic model. It shows that the R …
Shamsun Nahar, Florina Rahman, Mahrima Akter Mim
This paper presents an AI-integrated platform combining renewable energy and data analytics for corporate ESG compliance. It uses AI/ML for energy demand forecasting, carbon emission estimation, and automated ESG reporting aligned with inte…
Younes Gholizadeh
This paper proposes a low-energy blockchain approach using Proof of Elapsed Time (PoET) for carbon footprint tracking in EU countries. It compares traditional and blockchain-based approaches, demonstrating PoET's potential to optimize emiss…
C. Rao, Praveen Kumar Naidu Rayanki, Polepalli Rajeev Meenon +2
This paper proposes a privacy-preserving cross-chain federated blockchain-IoT framework for carbon credit management, integrating RFID-based emission data collection, IBC interoperability, and DP-FL for fraud detection and price prediction.…
Yiyu Zhao, Yaning Zhang, Xiaohan Wu +4
This study develops the Blockchain-enabled IoT-BIM Platform (BIBP) for real-time carbon monitoring in modular integrated construction (MiC). Validated on a 15-story MiC project in Hong Kong, BIBP establishes a baseline of 949.84 kgCO2e/m2 a…
Yijin Wang, Hongzheng Ma
This study finds that voluntary adoption of ISSB-aligned climate disclosure is positively associated with firm value (Tobin's Q) and operational performance (ROA) among Asia-Pacific listed firms. Using difference-in-differences models, the …
Jingyuan Ding, Yuan Lu
This paper proposes a hybrid IoT-Hadoop-blockchain architecture for decentralized Measurement, Reporting, and Verification (MRV) of greenhouse gas emissions. It redefines carbon data as a continuously governed digital asset, leveraging Hype…
Jingchao Sun, Hongming Na, Honggang Pan +7
This paper proposes an optimized decarbonization pathway integrated with a carbon trading mechanism for China's steel industry to achieve carbon neutrality. It models energy transition and technology choices in steel production, analyzing h…
Alessandro Franco, Wilfried Marius Simo Toukam
This study quantifies cement manufacturing's energy and emission baselines and evaluates decarbonization pathways including efficiency, alternative fuels, clinker substitution, electrification, hydrogen, and CCS. Hydrogen can reduce combust…
Luc Cot'e, Andy Sun
This paper proposes a market design for real-time electricity markets that integrates carbon accounting into grid operations via a two-layered dispatch mechanism. It defines locational marginal emissions (LMEs) and establishes analogs to th…
Czernichowski-Lauriol I.
This paper presents CO2GeoNet's actions in Europe to advance CCUS through global cooperation. It highlights technology development, policy recommendations, and international knowledge sharing to contribute to global decarbonization.
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