GX & Decarbonization Research

A. Pournaghshband, F. Piadeh, Mohsen Ahmadi +1

This study develops an AI-driven decision-support framework integrating LCA, scenario-based material substitution, mixture-of-experts neural networks, and sustainability optimization. Using a UK office building case study with 1500 scenario…

Vlatka Bilas, Tomislav Radoš, Lana Frkovic

This study examines whether ESG ratings provide useful information for credit risk assessment in an emerging EU member state, using Croatian firm data from 2024-2025. Combining econometric models and random forest prediction, the findings s…

M. Sri, Mrs. A. V. Harshika, L. Nasreen +2

This paper proposes a carbon trading platform leveraging AI and machine learning for real-time pricing, risk assessment, and emission reduction forecasting. It uses blockchain to ensure secure and tamper-proof transactions, offering a scala…

Rongchen Zou

This paper examines ESG rating frameworks embedded in FinTech tools such as AI-driven investment systems and credit-assessment algorithms. While ESG adoption improves transparency and long-term risk oversight, inconsistencies among rating p…

Shuangxiang Zeng, Lisha Dong, Jingtao Shao +2

This study optimizes carbon purification from spent cathode carbon (SCC), a hazardous waste from aluminum production, using machine learning. Six algorithms were compared, and LightGBM was tuned via RSM, orthogonal design, and local optimiz…

Kalpana K, Backiyavathy M R, Chitdeshwari T +2

This review introduces Engineered Soil Carbon Systems (ESCS), integrating enhanced weathering, engineered biology, nanomaterials, and digital monitoring. It highlights IoT and machine learning for improved MRV, positioning ESCS as a verifia…

W. -J. Bai

This study develops an early warning system for green transportation financial risks using PCA for dimensionality reduction and an improved PSO-optimized SVM. Integrating financial, environmental, policy, and market indicators, it achieves …

K. K. Qin, Yu Zheng, Chao Zeng +1

This paper proposes a low-carbon scheduling and carbon emission prediction framework for power grid construction machinery by integrating an improved genetic algorithm (IGA), deep reinforcement learning (DRL), and a gated recurrent unit (GR…

Fu Jia, Yingjie Ju, Robert D. Klassen +2

This study examines how China's carbon emissions trading schemes (CETS) affect firms' environmental and social (E&S) disclosure using an institutional theory framework. Exploiting staggered CETS implementation (2013-2024) as a quasi-natural…

Mitch D

This paper proposes OptimTwin, an integrated framework combining AI-driven digital twins and power system asset management to support long-term grid investment planning. Using IRENA FlexTool and a deep neural network surrogate on the IEEE/N…

Simon Utsu-Ingwu, Lloyd Endurance Ogbondamati

This study proposes a hybrid offshore energy system integrating wind, wave, and floating solar, controlled by AI-based predictive control (MPC and reinforcement learning). Simulations show smoothed output averaging 1567 kW, LCOE of 13.84-39…

Ewees A.A.

This paper proposes an optimized dendritic neural network (DNN) to predict the viscosity of CO2-N2 gas mixtures, providing accurate thermophysical data crucial for CCUS process design and operation. It demonstrates superior prediction accur…

Kim H.

This paper proposes a BERT-based text analysis method to assess the alignment of corporate ESG disclosures with the UN SDGs. By automatically classifying disclosure texts, it quantitatively measures corporate contributions to the SDGs, enha…

Shu Li, Yu Song, Zhongli Bai

This paper proposes a flexible arbitrage framework for co-located renewable-battery systems (RES-BESS) bidding in multiple electricity markets, using Soft Actor-Critic (SAC) and Temporal Convolutional Network (TCN) to autonomously decide ch…

Wattana Viriyasitavat, Phoranee Rhuwadhana, Ra-Pee Pattanapanyasat +5

This study conceptualizes digital infrastructure (DI) as a socio-technical design space where sustainability is embedded by design rather than assessed post hoc via ESG reporting. Using PRISMA-based systematic review and realist synthesis, …

Olamide Efosa-Austin, Olajuwon Ifalade, C. Asuquo +2

Aqua Intel™ is a digital optimization layer for produced water treatment in Nigeria's oil and gas sector, using linear programming to dynamically allocate water across treatment, reuse, and disposal pathways. A pilot simulation on a 25,000 …

Kalyani Singh, Vaibhavi Shahane, Mrunalini Khandare

This study quantitatively analyzes the impact of blockchain-enabled green finance on corporate sustainability and performance using panel data from Indian firms across sectors. Integrating stakeholder, institutional, and TOE frameworks, it …

Xirong Gao, Shiwei Wei

This study empirically examines whether supply chain finance (SCF) promotes corporate green innovation using data from Chinese A-share listed firms. Using patent data and text analysis, it finds a positive impact of SCF on green innovation,…

Wai Yie Leong

This paper proposes integrating ESG and GBI (Green Building Index) rating indicators into a BIM-based automated sustainability reporting system for Malaysian property developers. It aims to streamline reporting processes and improve data co…

Weina Zhu, Jiaxin Shen, Yixin Li +2

This study uses LDA topic modeling and fsQCA to identify pathways for carbon emission reduction in green buildings in China. It analyzes configurations of factors that lead to effective carbon reduction, offering insights for policy and des…