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 1–20 of 188 papers
Marco Cucculelli, Noemi Giampaoli, Matteo Renghini
This paper operationalizes the EU's Net-Zero Industry Act (NZIA) technology framework at the firm level, using large-scale web scraping to extract unstructured data from corporate websites and map Italian firms' adoption and development of …
Yan Luo
This study proposes an AI-driven ESG scoring framework using Slime Mould Algorithm (SMA) for feature selection and Random Forest Regressor (RFR) for prediction. With rigorous preprocessing, it achieves RMSE 0.3649, MAE 0.2538, and R² 0.9912…
Chenyan Wang, Yingying Jiang
This study proposes a data-driven, AI-assisted design framework for community low-carbon recycling terminals, combining K-means clustering and Kano-AHP to quantify user needs and prioritize design features. The developed terminal and platfo…
Kuanhou Tian, Le Sun
Using Chinese A-share listed firms from 2012-2023, this study finds institutional ownership is positively associated with absolute carbon emissions but negatively with emission intensity, with site visits strengthening monitoring. It highli…
Zixin Ma, Daliang Xu, Bobo Yang +6
Applies machine learning to synergistically optimize carbon emissions and contaminant removal in wastewater treatment plants. Proposes a control method that balances process efficiency and GHG reduction, contributing to carbon neutrality.
Yang Wang, Wenhao Chen, Mengyi Di +3
Proposes a blockchain-enabled game-theoretic carbon trading mechanism for shipping enterprises, combining a Stackelberg game between regulator and firms with a bidding game solved via no-regret learning. Simulations show reduced emissions a…
Rouzbeh Haghighi, Ali Hassan, Sina Mohammadi +2
This study models AI data-center load growth in a three-level Stackelberg-Bayesian game among regulator, ISO, and investors. It quantifies how carbon taxes and subsidies for renewables and second-life batteries reshape investment mix, emiss…
Chuanzhu Sun, Weiguang Zhang, Leixiang Peng +6
IRPVS is the first public dataset providing pixel-level instance segmentation masks for process-specific industrial soiling on rooftop PV systems. It includes 8,012 UAV images from an industrial park in China, annotated with three contamina…
Abdelrehim Awad, Bshair Alharthi, Hiyam Abdulrahim +5
This study proposes an MCDA framework to holistically assess AI-driven data centers in the GCC, comparing environmental impacts with dispersed AI sustainability benefits across sectors. Under business-as-usual, emissions rise substantially …
Huang, Bo, Yan, Yan, Lu, Jianan +1
This paper proposes TASR, a trustworthy LLM-based framework for TCFD-aligned sustainability report analysis. It integrates LLM-based scoring, benchmarking against third-party ESG ratings, and predictive modeling. Experiments on 100 U.S. oil…
Wang K.H.
This paper analyzes the dynamic mutual relationship between AI technology and the green finance market in China, examining whether AI acts as a driver or barrier to green finance development. Using dynamic models, it reveals the interaction…
Cheryl O. Tayo
This bibliometric study analyzes global development of intelligent technologies for blue carbon ecosystem monitoring, using 7,054 Scopus publications (1971-2026) with Bibliometrix and VOSviewer. It reveals accelerated growth post-2010, them…
Zhen Wang
This paper proposes a collaborative decision system for low-carbon navigation of multiple ships using federated learning (FL). By training models without sharing raw data, it reduces fuel consumption and CO2 emissions while preserving data …
Anelia Kurteva, Carlo van der Valk, Kathleen McMahon +2
To advance circular economy in ICT, the RePlanIT ontology supports building Digital Product Passports (DPPs) for laptops and data servers, integrating device, component, material, and CE knowledge. Validated in a real-world case aiding sust…
Nada Sahlab, Hossein Rimaz, Prerna Juhlin +2
This study explores the use of Asset Administration Shell (AAS) and knowledge graphs to incorporate sustainability criteria in early product design. An EPD submodel is represented in RDF, enabling direct comparison of environmental indicato…
Jochen Deuse, David Wagstyl, Victor Hernandez Moreno +3
This paper explores how green digital twins contribute to sustainable industrial production across the product life cycle. It highlights opportunities and challenges in revealing emissions and constructing green digital twins for various pu…
Linda Eckert, Ann-Sophie Finner, Daniel Heinz +1
This study uses backcasting to envision a circular automotive industry by 2050, aligned with the European Green Deal. It examines how digital technologies like AI, digital twins, and product passports enhance data sharing, traceability, and…
Hans-Dieter Wehle
This chapter examines how AI-enhanced Digital Product Passports (DPPs) can support ESG transparency in Industry 5.0. It proposes a modular software architecture combining machine learning for carbon forecasting, anomaly detection, and impac…
Fatemeh Stodt, Nicolai Maisch, Philipp Ruf +3
This paper proposes a blockchain-based concept for Digital Product Passports (DPP) to enhance sustainability in EU supply chains. It combines Secret Network and Gaia-X to enable secure, confidential sharing of carbon footprint and material …
Jérome Dierickx
The TRUSTEX project develops interoperable digital infrastructures for Digital Product Passports (DPPs) in textiles, addressing fragmented supply chains and lack of standards. It leverages PCDS (ISO 59040) and combines AI-driven data valida…
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