GX & Decarbonization Research

Amel Mahmood Ali Alobaidi

This study examines the impact of voluntary climate anxiety disclosure on investor behavior using mixed methods: textual analysis, archival data, and experiments. Disclosure significantly predicts investor behavior, moderated by firm size a…

Sinhika Deshmukh, S. Karve

This study proposes and evaluates a blockchain-enabled traceability framework for Tata Steel's supply chain. Scenario modeling suggests traceability coverage could rise from 42% to 98%, scrap reuse from 60% to 88%, enabling an estimated 3.0…

Wang-Chen Yang, H. Arian, Cui-Cui Luo

This paper proposes a constrained residual learning framework for portfolio optimization in China and Europe's carbon markets. It applies machine learning to capture carbon price dynamics and optimize risk-return trade-offs, offering improv…

Hannes Cordes

This systematic review maps NLP tasks used to analyze sustainability reports, categorizing 160 studies hierarchically. It finds keyword search, content analysis, and topic modeling are most common, and highlights limitations such as linguis…

Rongyu Ji

This qualitative case study of Microsoft examines how ESG information disclosure affects capital market performance in AI enterprises. It finds that completeness, openness, and AI-specific governance of ESG disclosure are high, with respons…

Léo Staccioli, José Gallego, Milena Nasner +1

This study assesses carbon footprint of defect repair in wind turbine blade manufacturing across three configurations: baseline, optimized infusion, and sensor+ML. Optimized infusion cuts repair CO2 by 30.4%, ML by 19.5%, less than its 32.1…

Atul Khanna, Abhishek Shukla

As AI workloads grow, data center electricity demand and carbon emissions rise sharply. This paper argues from an operations perspective—not hardware design—that workload placement, energy- and carbon-aware scheduling, right-sizing, inciden…

Oyetola Ogunkunle, Emmanuel Uche, Kinsgley I. Okere +1

This paper systematically evaluates AI contributions to low-carbon energy production using bibliometric analysis and SWOT appraisal. It identifies research trends, key themes, and strengths, weaknesses, opportunities, and threats, offering …

Bilal M, Latif F, Hasnain M +3

This paper systematically reviews the role of machine learning (ML) in designing Metal-Organic Frameworks (MOFs) for CO2 capture. It evaluates the latest models across four key areas: process-level application, mechanistic interpretable mod…

Islam MS, Sarkar J

Eco-ITAD is an on-premise system that diagnoses hardware health using S.M.A.R.T. telemetry and computes avoided Scope 3 emissions using DEFRA factors. It generates compliance certificates in volatile memory, eliminating persistent writes. E…

Surathunmanun, Surasak, Ongsakul, Weerakorn, Singh, Jai Govind +1

This paper proposes a novel framework (CTT–ViT–Transformer) integrating satellite cloud top temperature imagery with Vision Transformer and Transformer models for short-term solar PV forecasting in sensor-constrained microgrids. Evaluated o…

Huilu Jiang, He-Liang Zhu, Zichen Xu +1

This paper examines the impact of China's green factory certification on corporate digital-green collaborative transformation using panel data of A-share listed firms from 2012-2022 and a multi-period DID model. Certification significantly …

Stephen Oko Gyan Torto, Rupendra Kumar Pachauri, Jai Govind Singh +4

This review systematically classifies transactive energy management (TEM) in multi-vector multi-agent energy systems, analyzing market topology, agent interaction, game-theoretic models, and deployment challenges. It introduces TE-RM, a hyb…

Farinu Uthman, Philip Edward, Adekola Priscilla

This study develops a hybrid AI model integrating random forest, LSTM, and gradient boosting to forecast carbon sequestration and financial returns of afforestation projects. Using satellite, soil, carbon price, climate, and cost data, it g…

Arpit Darbari

Proposes a Unified Digital ESG Framework (UDEF) for manufacturing that integrates CSRD/ESRS compliance, GHG Protocol-based accounting, and SDG alignment. Leverages smart metering, IIoT, cloud EMS, and AI-assisted decision support for contin…

Hermanus, Davy Ronald

This study proposes an AI-driven situational awareness architecture for citywide energy governance, integrating digital twins and multi-drone verification. Simulations show reduced false anomaly confirmations from 16% to 6%, improved Situat…

He Jiang, Rongyu Cao

This paper proposes an explainable time-varying feature selection method for predicting EU ETS carbon prices. It uses AI/ML to dynamically identify key drivers, balancing predictive accuracy with interpretability. Empirical analysis on EU E…

Chao He, Yunjie Su, Sirui Zhang +2

This review systematically examines the use of large language models (LLMs) in low-carbon smart energy systems, focusing on cloud-edge power IoT. It analyzes five technical themes: task offloading, dynamic edge resource allocation, low-late…

Archie Nathanael Mulyawan, Nataniella Eva Kezia, Verena Jesslyn Utama +1

This qualitative study examines how accountants, as ESG analysts and strategic leaders, enhance sustainability report transparency using the Susteineri system integrating IoT and AI. Real-time data collection enables monitoring of carbon em…

Pothin F

Using staggered difference-in-differences on SBTi and CDP data (2015-2023), this study finds that pledging firms expand their measurement boundary: within four years they report 2.5 more Scope 3 categories, lifting reported Scope 3 emission…