GX Research Hub · English
GX & Decarbonization Research
This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Peer-reviewed🇨🇳 ChinaJournalSustainability2026#AI × ESGDOI
Unraveling the Spatiotemporal Patterns and Potential Influencing Factors of County-Level Agricultural Carbon Emissions in Guangdong Province Using Interpretable Machine Learning
Guowei Wu, Manxuan Mao, Jie Zhi +4
This study analyzed spatiotemporal patterns and drivers of county-level agricultural carbon emissions in Guangdong, China (2000-2022), using an interpretable machine learning framework (Random Forest + SHAP). Emissions decreased by 22.9%, w…
Preprint🌍 GlobalResearch Square2026#AI × ESGDOI
Assessing the Credibility of Corporate SDG Claims: An Agentic AI Framework for Sustainability Report Analysis
Damrongsak Naparat, Erboon Ekasingh
This paper proposes an agentic AI framework to assess the credibility of corporate SDG claims by analyzing sustainability reports. It automatically verifies alignment between claims and actual actions, contributing to greenwashing detection…
Peer-reviewed🇪🇺 EuropeJournalCarbon Balance and Management2026#AI × ESGDOI
Modelling forest carbon stocks on the Canary Islands
Rüdiger Otto, Juan José García‐Alvarado, Elena Rocafull +6
Presents the first high-resolution forest carbon map for the Canary Islands integrating field data, ALS, Sentinel-2, and climatic variables with machine learning. Estimates 10.26 Tg carbon; laurel forests have exceptional densities. Structu…
Peer-reviewedJournalComputers and Electronics in Agriculture2026#AI × ESGDOI
Intelligent red-blue supplemental lighting control system for greenhouses: balancing photosynthesis and carbon footprint
Yuanyi Niu, Liang Zheng, Yajuan Chang +7
This paper proposes an intelligent red-blue supplemental lighting control system for greenhouses that balances photosynthesis and carbon footprint. Using AI/machine learning, it optimizes the light environment to reduce energy consumption w…
Peer-reviewed🇨🇳 ChinaJournalEnergies2026#AI × ESGDOI
Safety-Constrained Deep Reinforcement Learning for Source–Load–Storage Coordinated Operation of Green Low-Carbon Data Centers
Shi Zheng, Min Xu, Ziyu Fu +5
This study applies safety-constrained deep reinforcement learning to optimize the coordinated operation of green data centers, integrating renewables, grid, batteries, cooling, and computing loads. It formulates the problem as a constrained…
Peer-reviewedConferenceProceeding 2026 IEEE 6th International Conference on Computing Power and Communication Technologies Ic2pct 20262026#AI × ESGDOI
The Role of Artificial Intelligence and High-Performance Computing to Enhance the Efficiency of Green Finance
Kaushik P.
This paper explores the use of AI and high-performance computing to improve the efficiency of green finance, likely involving automation of ESG ratings, carbon accounting, and green bond screening. No abstract is available, but the title cl…
Peer-reviewedJournalEnvironmental Science and Technology2026#AI × ESGDOI
Can Data Mining Improve Methane Correction Factors for Urban, Nonsewered Sanitation?
Vogel M.
This paper investigates whether data mining can improve methane correction factors (MCFs) for urban nonsewered sanitation systems. By applying machine learning to empirical data, it aims to derive more accurate emissions estimates, enhancin…
Peer-reviewedJournalPhysics and Chemistry of the Earth2026#AI × ESGDOI
Artificial intelligence in wastewater treatment and resource recovery towards net-zero water resource recovery facilities
Edo G.I.
This paper explores the application of artificial intelligence (AI) in wastewater treatment and resource recovery to achieve net-zero water resource recovery facilities. AI techniques optimize energy consumption and enhance resource recover…
Peer-reviewed🌍 GlobalJournalInternational Workshop on Engineering Multi-Agent Systems2026#AI × ESGDOI
Digital Transformation and Corporate Social Responsibility for Impact Measurement: A Literature Review
Edralene M. Toñacao, Anik Yuesti, J. Alve
This integrative literature review examines how digital technologies (AI, big data, IoT, blockchain) influence CSR impact measurement, distinguishing it from sustainability disclosure and ESG ratings. Five interdependent dimensions are iden…
Peer-reviewed🇨🇳 ChinaJournalJournal of Forecasting2026#AI × ESGDOI
Synergizing Spatial and Temporal Dynamics for Carbon Price Forecasting: A Heterogeneous Ensemble Approach
Yantong Zhao, Gaoxiu Qiao
This paper introduces a heterogeneous ensemble framework for European carbon price forecasting, integrating LASSO for variable selection, MEMD-ARIMAX-mLSTM for temporal dynamics, and GWnet-attn for spatial dependencies. Empirical results sh…
Peer-reviewed🇨🇳 ChinaJournalSustainable Development2026#AI × ESGDOI
Forecasting Carbon Emissions With External Drivers: Comparative Linear–Machine Learning Models With Global Change Assessment Model ( <scp>GCAM</scp> ) Mitigation Scenarios in West Africa
Temidayo Alex‐Oke, Olusola Bamisile, Joseph Junior Nkou Nkou +3
This study develops a comparative framework using SARIMAX, Random Forest, Transformer Encoder, and Attention-Gated GRU to forecast CO2 emissions for 16 West African countries. Attention-based models achieve the best performance (MAPE 6.14%-…
🌍 GlobalDatasetZenodo (CERN European Organization for Nuclear Research)2026#AI × ESGDOI
A Framework-Guided Approach for Assessing Corporate Climate Disclosure Quality and Sustainability Reporting using ClimateBERT and Sentence Transformer Embeddings
Aditya Narayan, Arghya Chakraborty, Santosh Kumar Mishra +1
This paper proposes a framework-guided approach using ClimateBERT and Sentence Transformer embeddings to assess corporate climate disclosure quality, defining a Climate Disclosure Quality Index (CDQI). It provides a dataset for automated sc…
Peer-reviewedJournalCumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi2026#AI × ESGDOI
ANALYSIS OF PRICE DYNAMICS OF BLOCKCHAIN-BASED CARBON CREDIT TOKENS IN THE CRYPTOCURRENCY MARKET USING DEEP LEARNING METHODS
Aynur İNCEKIRIK
This study analyzes the price dynamics of blockchain-based carbon credit tokens (BCT, MCO2, KLIMA) using deep learning methods (LSTM, GRU, transfer learning) with daily data from Oct 2021 to Nov 2025. Findings show strong internal correlati…
Peer-reviewedCNJournalAnalytical Chemistry2026#AI × ESGDOI
Process-Aware Deep Learning for Low-Cost Greenhouse Gas Sensing: Insights from Composting toward Scalable Anthropogenic Activities Applications
Zhonghao He, Haihong Jiang, Jing He +7
This paper proposes a process-aware deep learning approach for low-cost greenhouse gas sensing. Using composting as a case study, it incorporates process information to improve sensing accuracy. The method is scalable to other anthropogenic…
Peer-reviewed🌍 GlobalJournalBusiness Strategy and the Environment2026#AI × ESGDOI
Discursive Governance and Development Goals: A Performative Theory of Corporate Purpose in Sustainability Discourse
Augustine Okeke, Ifeanyi Ugbebor
This study introduces the SDG-Purpose Alignment Index (SPAI), a computational construct quantifying how CEO letters align thematically, tonally, and stylistically with specific SDG targets. Analyzing 740 CEO letters from 148 listed firms ac…
Peer-reviewed🇨🇳 ChinaJournalApplied Spatial Analysis and Policy2026#AI × ESGDOI
Scale-Dependent and Non-linear Effects of Land-Cover Configuration on Carbon Performance: an MGWR-SHAP Analysis of Tianjin
Jiaxiang Wang, T X Chen
This study uses MGWR-SHAP analysis to evaluate the scale-dependent and non-linear effects of land-cover configuration on carbon performance in Tianjin, China. It reveals that different land cover types have varying impacts at different spat…
PreprintZenodo (CERN European Organization for Nuclear Research)2026#AI × ESGDOI
Energy Transparency in Open-Source AI: Training Carbon Footprints and Power Consumption Reporting Standards
Олег Ивченко, Iryna Ivchenko
This paper proposes reporting standards for energy consumption and carbon footprint of open-source AI training. It presents specific metrics and methodologies to enhance transparency, contributing to decarbonization in the AI sector.
Peer-reviewed🇨🇳 ChinaJournalMathematics2026#AI × ESGDOI
A Temporal Dendritic Neural Model for Carbon Emission Forecasting
T Zhang, Ting Jin, Kang Wu +1
This paper proposes a Temporal Dendritic Neural Model (TDNM) with a Dendritic Adaptive Learning algorithm for multivariate carbon emission forecasting. Using panel data from 54 Chinese cities (1999-2023) with 13 driving factors, it outperfo…
🇨🇳 ChinaJournalZenodo (CERN European Organization for Nuclear Research)2026#AI × ESGDOI
Environmental screening of carbon-water trade-offs in geo-distributed AI workload allocation: reproducibility artifact
Q Zhang, 胜生 余, Tongna Liu
This paper provides a reproducibility artifact (v2.0.0) for an environmental decision model evaluating carbon-water trade-offs in geo-distributed AI workload allocation. It includes portable Python code and test data, supporting only scenar…
Peer-reviewedJournalEuropean Journal of Sustainable Development Research2026#AI × ESGDOI
ESG in transition: A text mining analysis of how Indian corporations evolved from checkbox reporting to strategic integration
Priyanka Aggarwal, Archana U Singh, Deepali Malhotra
This study analyzes sustainability reports of 269 NIFTY 500 firms from FY2015-2023 using text mining. It identifies three phases of ESG reporting evolution: initial establishment (2015-17), governance consolidation (2018-20), and balanced i…