GX & Decarbonization Research

Trésor Ndengo Tietia, Rostin Mabela Matendo Makengo, Pierre Kasengedia Motumbe +4

This paper proposes a smart network resource management model using AI (DQN, Q-Learning, PSO, ACO) to optimize energy consumption of IT infrastructures in the Democratic Republic of Congo. Simulations show up to 32% energy reduction and 21.…

Saher Elsayed

This paper presents the first phase-resolved carbon footprint characterization of RLHF, finding that the PPO phase accounts for 59-64% of total training emissions. It introduces CarbonAware-RLHF, a scheduling framework that adaptively shift…

Q Zhang, 胜生 余, Tongna Liu

This reproducibility artifact provides portable Python code, derived inputs, frozen results, and tests for a carbon-water trade-off analysis in geo-distributed AI inference allocation under water-stress screening. It enables verification of…

Niko Firzi Anansyah, Ratu Mutiara Siregar, Andi Prayogi +1

This study develops an automated ESG reporting system for the palm oil industry using a dual-LLM architecture (Groq Llama 3 primary, Gemini backup). It introduces a programmatic constraint that caps the ESG score at 50 if Ganoderma infectio…

Krisztina Finta, Csaba Dezső Dér, Klaudia Gabriella Horváth +1

This study investigates the sustainability paradox in AI-driven short-form video marketing, revealing that video generation consumes ~30x more energy than image creation. It models that a mid-sized team producing 2,500 AI videos annually em…

Saheed A. Adeniyi, Adeyemi A. Adefisan-Williams, Rukayat Abisola Olawale, Daniel O. Olokpo and Elizabeth I. Igbodor

This study develops a digital twin coupling a physics-based drying-kinetics engine with an autoencoder-driven predictive maintenance engine for a hybrid solar-electric dehydrator in tropical Nigeria. It predicted moisture ratio with RMSE 0.…

Damla Yalçıner Çal, Ecir Uğur Küçüksille

This study uses the EDGAR dataset (1970-2023) to forecast GHG emissions with LSTM and Transformer models. While LSTM captures long-term trends, it underperforms a naive benchmark under regime changes. Transformer shows improvement for the l…

Jiachen Shou, Waner Li, Hui Li +5

This study integrates Random Forest and DEMATEL to identify key drivers of transportation carbon emissions across 30 Chinese provinces from 1997 to 2022. Findings show that R&D expenditure, registered scientific achievements, and energy con…

Shimei Li, Yuqing Li, Jinman Luo +1

This paper proposes a dynamic optimization strategy for carbon emissions in an electrocarbon coupling system using reinforcement learning. The approach enables real-time emission reduction, outperforming static methods. It contributes to sy…

Omar Nassar, Fahimeh Jafari, David King

This paper presents KG-ESG, an AI-driven proof-of-concept that converts public ESG news into structured, queryable knowledge graphs. It processes 1,098 news articles for 450 FTSE 100/250 and ASX 200 companies using NER, sentiment analysis, …

Mai-Phuong Nguyen, Minh Thi Ngoc Trieu

Using a panel of Vietnamese manufacturing firms from 2018-2024, this study finds that digital transformation positively impacts ESG performance, but the effect is weaker for state-owned enterprises. The analysis employs text-mining methods …

Cande Lian, Wentao Zeng, Jiabin Wu +10

This paper proposes FGDSE, an interpretable causal-ensemble framework that predicts EV charging station fault risk under climate stress (extreme heat, heavy precipitation, humidity). Using 25 months of data from 13 stations, it outperforms …

Yuhui Lyu, Fan Zheng, Haodong Ji +1

This study presents a machine learning-driven multiobjective optimization framework for ultrahigh-performance concrete (UHPC) mix design to balance strength, cost, and embodied carbon. Using LightGBM predictive models, single-objective and …

Mahantesh.H.M, Mandeep Narang, R.Padmapriya +3

This paper presents GreenSynapse, a cognitive AI-driven platform integrating neuro-symbolic reasoning, digital twins, and blockchain for sustainable smart cities. It uses reinforcement learning and symbolic reasoning to adaptively control e…

M. Kayakuş, Mustafa Terzioğlu, Dilşad Erdoğan +3

This study applies a multi-method NLP framework to analyze green finance discourse on social media. Using TF-IDF, FinBERT sentiment analysis, LDA topic modeling, and keyword co-occurrence networks on 23,452 X posts, it finds that discourse …

M. Raslan, M. Mostafa, Ahmed S. Abdellah +2

This paper proposes a Demand Side Management strategy using Non-Intrusive Load Monitoring (NILM) to optimize green hydrogen microgrid costs. By identifying and shifting deferrable appliances (dishwasher, washing machine) from evening peak t…

Francesco Smaldone, Benedetta Esposito, Daniela Sica +1

This study profiles employability skills needed for the climate-circularity nexus in agri-food using large-scale text mining and LLM-based classification of job ads. Findings highlight the prominence of transversal skills, growing demand fo…

Sohan Kumar Jha, Nirmala Kushwah

This paper critically examines AI's role in sustainable finance and green banking. It develops an integrated conceptual model linking AI capabilities to ESG integration, climate risk analytics, green credit allocation, and portfolio managem…

Krasteva-Hristova R

This exploratory study analyzes the 2024 UK transparency reports of Deloitte, EY, KPMG, and PwC to assess governance disclosures for AI-assisted professional judgment in audit and sustainability assurance. It develops a seven-dimension AI-J…

Kodela, Kalyan Chakravarthy, Roy, Stabak, Ghorbanzadeh, Shaghayegh +2

This paper proposes the Spatio-Temporal Graph Multi-Agent Carbon Flux Model (STG-MACFM), a learning-driven framework within a GeoAI-enabled digital twin. It uses hierarchical agents, reinforcement learning, and graph attention networks to d…