GX & Decarbonization Research

C Zhao

This paper proposes a carbon management optimization method using blockchain to enhance transparency and traceability of Scope 3 emissions, focusing on marginalized large-scale operators. It ensures tamper-proof data and improves reliabilit…

Supreetha HD, Punith Cariappa, Suresha B

This review systematically analyzes how Industry 4.0 technologies (IoT, AI, big data, etc.) integrated with Circular Economy principles enhance Triple Bottom Line performance in industrial firms. It finds significant improvements in environ…

Paula Marielle Ababao, Ian B. Benitez, Gabriel Avelino Sampedro

This study proposes a blockchain-integrated circular economy framework to enhance lifecycle tracking and emissions reporting for maritime ICT and energy materials. It combines Digital Product Passports, IoT telemetry, and smart contracts to…

Tobias Ströher

This cumulative dissertation investigates how digital MRV (Measuring, Reporting, and Verification) can transform GHG emissions management within and across organizations, drawing on AI, data spaces, digital identities, and distributed ledge…

「European Green Strategic Development Committee, 「European Green Strategic Development Committee

Reports iterative development of a carbon removal system to V8.0. Fully rewrites reaction database, kinetics, byproduct prediction, spectral/imaging detection, risk assessment, and strategy learning; adds new modules for atmospheric diffusi…

Reza Kiani Mavi, Majid Semiari, Seyed Ashkan Hosseini Shekarabi +4

This study develops an integrated optimization framework for designing a sustainable three-echelon food supply chain (suppliers, manufacturer, retailers), minimizing cost and carbon emissions while maximizing certified green output. Governm…

Haya R. Hasan, Khaled Salah, Ahmad Mayyas +4

This paper proposes a decentralized blockchain-based digital passport for EV batteries using composable NFTs, ensuring traceability and tamper-proof records across the supply chain. It evaluates four cathode chemistries using ten sustainabi…

Xinyue Hao, Emrah Demir

This study identifies triggers and inhibitors of AI adoption in supply chains using a PRISMA systematic review and thematic analysis under the ESG framework. Environmental triggers include waste and GHG reduction; social triggers include pr…

Afia Saiara Akhi, Mustakim Jahan, Shamima Shammay +1

This systematic review synthesizes recent research on AI-driven optimization for sustainable project and supply chain management, covering predictive analytics, machine learning, digital twins, and multi-objective optimization. It identifie…

Prathaban Durai, Jagannath Nalavade

Proposes a data monitoring framework for aerospace Scope 3 emissions using big data analytics, supporting batch and real-time inputs. Enables airlines to track emissions, set targets, and develop reduction strategies, providing insights for…

Joan van Eeckhout, Miona Dimic, Cecilio Ángulo

Agrixel is a new interoperable geographic standard for agricultural data, leveraging AI and machine learning to integrate externalities like carbon footprint, energy use, and water management. It supports FAIR data principles and aims to en…

Duncan J. Reynolds

This paper reveals that AI-related carbon emissions are largely omitted from NHS mandatory Green Plan reporting. It identifies three gaps: lack of granularity obscuring AI workloads' energy intensity, exclusion of hardware lifecycle emissio…

Duncan J. Reynolds

This paper reveals that AI-related carbon emissions are largely omitted from mandatory NHS Green Plan reporting. Current Scope 1-3 accounting misses emissions from AI workloads' energy intensity, hardware life-cycle (e.g., GPUs), and unproc…

Girish K A, Chiranthana Shreya, Nischitha H E +2

This paper presents an autonomous robot using AI and image processing to detect plants and spray fertilizers precisely. It reduces chemical waste and farmer exposure, enhancing sustainability. Experiments demonstrate improved spraying accur…

Yinfeng Chen, Ying Hu

Using panel data from China's carbon-intensive industries (2007-2023) and double debiased machine learning, this study shows that GVC participation and domestic content ratio promote low-carbon innovation. Mediation paths include upgrading …

Wen‐Chi Yang, Wen‐Min Lu, Irene Wei Kiong Ting +1

This study analyzes 37 firms in TSMC's value chain using inverse DEA and chance-constrained DEA to examine ESG initiatives' impact on eco-efficiency. Environmental dimension negatively affects eco-efficiency, while social and governance dim…

Çağdaş Civelek

This study compares Türkiye's agricultural GHG emissions with EU-27 countries and forecasts 2025-2030 emissions using machine learning. Agricultural emissions account for ~12% of total, ranking second in total but ninth lowest in intensity.…

Elena Claudia BADEA (FLOREA), A. Olteanu (Burca), M. Bunea +1

This study proposes an integrated competency framework for auditors in the AI era, expanding roles from financial audit to ESG assurance and AI tool use. Based on a structured literature review of 22 articles (2019-2025), it identifies six …

Hwang S.

This paper proposes an LLM-agent framework to automatically assess IFRS S2-aligned climate disclosures in Korean corporate ESG reports. It aims to efficiently check completeness and consistency, identifying disclosure gaps. Contributes to t…

Naila Rana Andira, Philipp Sander, A. Pehlken

Industry accounts for three-quarters of global GHG emissions, and procurement changes affect product emissions. This paper integrates an event-based architecture with ERP systems to dynamically calculate and visualize material GHG emissions…