GX & Decarbonization Research

Vijay Kumar

This paper examines the dual role of AI in sustainability: as an enabler of resource efficiency and green transition, and as a consumer of energy and resources. It discusses the Green AI movement prioritizing energy-efficient algorithms ove…

Deepak Gupta, Ziyodullayev Sodiq, Matkarimov Mansur +4

This chapter examines the convergence of AI and climate finance, exploring machine learning for climate risk modeling, deep learning for ESG rating accuracy, NLP for climate disclosure extraction, and predictive models for transition risks.…

Pradnyesh Khairnar , Karishma Rathod and Asst. Prof. Dineshwari Bisen

This paper proposes the Green Data Center Framework integrating renewable energy, advanced thermal management, and AI-driven resource optimization. Three pilot sites demonstrate PUE of 1.2, 75% renewable energy coverage, 50% reduction in se…

Hafiane, Doha El, Magri, Abdelmounime El, Myasse, Ilyass El +2

This paper proposes a real-time energy management framework for hybrid low-voltage microgrids using multi-agent systems (MAS). Co-simulated with JADE and MATLAB/Simulink, the approach increases renewable energy utilization by 10% and reduce…

Han-Teng Liao, Karen Ang

This paper proposes a regenerative socio-technical roadmap for AI infrastructure that addresses Scope 3 emissions and e-waste by integrating IEEE IRDS sustainability considerations. It reframes AI as a system-of-systems governed by planetar…

Xueyang Li, Jin Ma

This study examines the impact of green finance on city-level carbon intensity using econometric models and machine learning (SHAP) on data from 285 Chinese cities. Green bonds and green investment show the strongest decarbonization effects…

Rimi Gusliana Mais, Munir Munir

This study proposes an AI-driven carbon accountability framework integrating real-time emissions data, financial flows, and governance mechanisms. Using Indonesia as a case, it demonstrates how AI enhances transparency and efficiency in cli…

Fateh Belaïd

This paper analyzes over 1200 peer-reviewed studies on clean cooking and electricity access using computational topic modeling. It finds that only 57.6% of publications quantify impacts beyond access, and only the health and household air p…

Saqib Munir, Mushab Rashid, Abdul Ghaffar

Using Chinese data from 1999-2023, this study examines the association between environmental accounting indicators, government R&D expenditure, and renewable energy adoption via ARDL and machine learning. Regulatory quality has a positive l…

Samruddhi Pandit, Anuja Mukherjee, Rugved Dani +1

This paper proposes a five-layer AI-enabled smart agriculture framework for climate-resilient and sustainable food systems. It integrates climate inputs, sensing, predictive analytics, decision support, and sustainability outcomes. Case stu…

Shijie Ma, Jingzhi Hou, Haoran Niu +1

Using a debiased machine learning framework and causal forest analysis on Chinese high-emission listed firms (2009–2024), this study reveals a 'threshold-trigger' mechanism: once climate pressures exceed firm endurance, companies shift to s…

Xiaolong Zhang, Congjun Rao, Abdulrahman Almandeel +2

This paper proposes a spatiotemporal graph-based grey model incorporating fractional calculus to improve greenhouse gas emission forecasting, potentially outperforming traditional methods.

Feng Gao, Maoying Deng, Xingdong Deng +6

This paper proposes a framework integrating explainable AI and clustering to decouple passenger and freight transport emissions in urban areas. It enables precision governance by identifying distinct emission patterns, supporting targeted d…

Zhuokai Zhou, Sizhuo Wang

This study uses a hybrid forecasting framework incorporating machine learning to analyze predictive linkages between carbon markets and coking coal futures. It provides implications for market efficiency and highlights the interconnection b…

Jun Lyu, Yu Shu, Shuo Wang

Using unsupervised machine learning (LDA topic modeling, semantic network analysis, and hierarchical clustering) on subtitle transcripts from 60 YouTube green energy documentaries, this study identifies three framing communities: Technologi…

Noah Lund Syrdal, Anders Vestrum, Jörgen Bergh

This paper proposes a carbon-aware re-ranking strategy for e-commerce recommendations. It estimates missing product carbon footprints using a retrieval-augmented pipeline with LLM and semantic similarity, then applies a tunable re-ranking o…

Harshal Gavali, Apurva Jangle, Asiya Attar +2

This paper systematically reviews the application of AI in climate change mitigation and adaptation, covering climate modeling, explainable AI, and regulatory compliance. It proposes the Climate Intelligence Integration Model (CIIM), a gove…

Dwi Nova Wijaya, Rommy Mochamad Ramdhani, Dewi Fitrotus Sa’diyah

Using panel data of 3,794 Indonesian listed firms (2018-2024), this study analyzes how narrative and quantitative ESG disclosures affect firm value (Tobin's Q). Quantitative disclosure significantly increases firm value, while narrative alo…

Samia Elattar

This paper proposes an AI framework for carbon-aware production scheduling that integrates environmental and public health co-benefits, enabling efficient emission reductions for industrial decarbonization.

A. Sunitha, K. Srinivas, T.Radhika, B.Chandrakala Naik, P. Sandya Rani

This study empirically analyzes the impact of AI, big data, and fintech adoption on sustainability reporting quality and corporate transparency using PLS-SEM on a sample of 312 professionals from India, UAE, and UK. All three digital constr…