GX & Decarbonization Research

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…

Chuan Chen, Huanhuan Ren, Chen Liu +6

To address data fragmentation and inaccuracy in carbon footprint accounting for EV traction batteries, a trusted data space architecture was developed, improving data integration efficiency by over 65% and reducing accounting error from 18%…

「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…

(著者不明)

This paper proposes an accessible carbon accounting framework for SMEs, integrating simplified emission tracking, cloud-based data management, and modular reporting templates. Machine learning enhances data accuracy, reducing reporting cost…

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…

Danhui Lai, Zhang Zeqi, Yingjie Li +2

This paper applies the FP-Growth association rule algorithm to product carbon footprint (CFP) certification data sharing and tracing, extracting emission-related rules across supply chain nodes. Compared with the Apriori method, it reduces …

Y.S. Cho, Arbind Agrahari Baniya, Kieran Murphy

This study proposes a traceability framework for horticulture using global data standards to capture on-farm events with decentralized identification and secure sharing. Tested on Victorian farms and an international export pilot, it suppor…

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…

Tao Wang, Yang Shen

Using panel data of Chinese A-share listed firms (2013-2023) and double machine learning, this study finds that supply chain digitalization (SCD) significantly improves enterprise green transformation performance (EGTP). Effects are stronge…

Lukas Nagel, Rainer Gerstbauer, Levon Harutyunyan +3

This paper proposes a data-provision method to predict carbon footprints across supply chains during the strategic planning stage of product development, aligning with EU climate neutrality goals. Leveraging the Gaia-X data infrastructure, …

Zhouhui Zhang, xinyu Liu, Xin‐Rong Zhang

This paper addresses energy consumption and environmental issues in agricultural cold chains, proposing AI and IoT for energy saving and low-carbon operations. It notes refrigeration accounts for ~80% of energy use and cold transport emits …

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…

Manuel Reif, Christiana Plociennik, Mohammad Hossein Rimaz +2

This paper proposes a Digital Product Passport (DPP) combining Gaia-X principles with the Asset Administration Shell, enabling interoperable access to product data via distributed submodels. Demonstrated through a practical Scope 3 carbon f…

Srikanta Routroy, Prasanta K. Sahu, Prem Chhetri

This editorial introduces a special issue on decarbonizing logistics and supply chains, highlighting strategies such as digital technologies, renewable energy, and circular economy. It emphasizes AI-driven decision support systems for reduc…

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…

Wang Jingqi, Gao Yan†, Wu Zhiqiang, Li Renjie

This paper proposes a real-time pricing model incorporating load uncertainty and carbon trading in smart grids, maximizing welfare for both supply and demand. Using Q-learning to handle non-convex nonlinear problems, it contributes to renew…