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-reviewedJournalFrontiers in Environmental Science and Sustainability2026#AI × ESGDOI
Lifecycle Assessment of Sustainable Construction Materials in Green Buildings: A Multi-Objective Optimization Model
Arthur J. Sterling, Marcus P. Thorne, Julian T. Harrow
This paper integrates Lifecycle Assessment with a Multi-Objective Optimization model using a genetic algorithm to select sustainable construction materials. Applied to a mid-rise commercial building, it simultaneously minimizes lifecycle co…
Peer-reviewedJournalInf.2026#AI × ESGDOI
AI-Enabled System-of-Systems Decision Support: BIM-Integrated AI-LCA for Resilient and Sustainable Fiber-Reinforced Façade Design
M. Al-Jamal, Ayooub Alsarhan, Wafa' Q. Al-Jamal +4
This study presents a digital-twin-ready decision-support framework integrating BIM and AI-enhanced LCA. Machine learning surrogate models (Random Forest, Gradient Boosting, ANN) predict mechanical performance and lifecycle indicators (CO2,…
Peer-reviewed🌍 GlobalJournalBuildings2026#AI × ESGDOI
The Rise of AI-Enabled Startups in Creating a Low-Carbon Built Environment
F. Pacheco-Torgal
This paper systematically reviews the role of AI in decarbonizing and enhancing resilience of the built environment. It maps AI applications across the building lifecycle—including generative design, predictive maintenance, digital twins, a…
Peer-reviewedJournalSmart and Sustainable Built Environment2026#AI × ESGDOI
Guiding early building design towards lower carbon emissions through set-based design and genetic algorithm optimisation
Linda Cusumano, Mats Granath, N. Olsson +1
This study integrates set-based design with genetic algorithm (NSGA-II) optimization to simultaneously minimize cost and embodied carbon in early building design. Applied to a reference building, the genetic algorithm alone reduced carbon b…
Peer-reviewedJournalE3S Web of Conferences2026#AI × ESGDOI
Automated IFC Generation and Machine Learning-Based λ-Correction for Embodied Carbon Estimation of Buildings
Chanhyeok Kang, Bokyung Jung, Taekyu Lee +2
This study proposes a practical framework for estimating embodied carbon in buildings using automated IFC model generation and machine learning correction. With minimal inputs (gross floor area, floors, etc.), baseline emissions are compute…
Peer-reviewedJournalBuilt Environment Project and Asset Management2026#AI × ESGDOI
An early-stage embodied carbon assessment method for the Global South: Sri Lankan case study
A. Nawarathna, Zaid Alwan, Barry J. Gledson +1
This study develops a multiple linear regression model for early-stage embodied carbon (EC) estimation using data from 25 office buildings in Sri Lanka. Gross internal floor area (GIFA) and external wall area (EWA) are the most influential …
Peer-reviewedCNJournalEnergies2026#AI × ESGDOI
Coordinated Scheduling of Carbon Capture, Renewables, and Storage in Bulk Carriers: A Dual-Timescale LSTM-Powered Multi-Objective Energy Management System Strategy
S. Ren, Min Chen
This study proposes a data-driven scheduling strategy for the Ship Integrated Energy System (SIES). Using LSTM for fuel consumption prediction and NSGA-II for multi-objective optimization, it simultaneously reduces CO2 emissions and costs. …
🌍 GlobalMaterials Research Proceedings2026#AI × ESGDOI
Multimodal Logistics Optimization Powered by AI for Green Hydrogen Export Corridors: An Internet of Energy Perspective on Morocco Europe Trade Routes
Raoua NACEIRI MRABTI
This paper applies AI-based optimization to green hydrogen export corridors from Morocco to Europe. Using machine learning on simulated data for road, pipeline, and sea transport, it finds that trans-Mediterranean pipelines are the most cos…
Peer-reviewedCNJournalProcesses2026#AI × ESGDOI
A Machine Learning-Enhanced Tri-Objective Stowage Optimization Framework for Low-Carbon Finished Steel Maritime Supply Chains
Bin Xu, Luyang Wang, Tingting Xiang +1
This study proposes a machine learning-enhanced tri-objective optimization framework for stowage planning of finished steel maritime logistics. It simultaneously maximizes deadweight utilization and minimizes carbon emissions, achieving 99.…
Peer-reviewed🇺🇸 USAJournalarXiv.org2026#AI × ESGDOI
Physics-informed offline reinforcement learning eliminates catastrophic fuel waste in maritime routing
Aniruddha Bora, J. Chalfant, C. Chryssostomidis
International shipping accounts for ~3% of global GHG emissions, but routing remains heuristic. This paper presents PIER, an offline reinforcement learning framework integrating physics-informed state construction, that reduces mean CO2 emi…
Peer-reviewed🌍 GlobalJournalSustainability2026#AI × ESGDOI
AI, Maritime Decarbonization, and Ocean Conservation
M. Spalding
This paper comprehensively examines AI's role in maritime decarbonization and ocean conservation. It analyzes applications in voyage optimization, wind-assisted propulsion, vessel automation, port coordination, predictive maintenance, ship …
Peer-reviewed🇪🇺 EuropeJournalRemote Sensing2026#AI × ESGDOI
Remote Sensing and AI-Based Monitoring of Soil Properties for Tier-3 MRV Framework of Complex Mediterranean Agroforestry Systems
Dimitra Palantza, Konstantinos Karyotis, Judit Torres Fernández del Campo +2
This study develops a hybrid machine learning and remote sensing framework for high-resolution soil organic carbon (SOC) mapping in Mediterranean agroforestry systems. Using Sentinel-2 data and environmental covariates, the model achieves R…
Peer-reviewedJournalEnergy Conversion and Management: X2026#AI × ESGDOI
Algorithmic intelligence for industrial decarbonization: a comparative analysis of meta-heuristic optimization versus commercial solvers in designing resilient hybrid microgrids
Md. Fardous Hasan Bappy
This paper compares meta-heuristic optimization algorithms with commercial solvers for designing resilient hybrid microgrids aimed at industrial decarbonization. It analyzes how AI-driven optimization can enhance energy efficiency and cost …
CNJournalOSF Preprints (OSF Preprints)2026#AI × ESG
Spatial Spillover Effects and Dynamic Evolution of Agricultural Carbon Sinks Under China’s Dual-Carbon Goals
Adekola Priscilla
This study analyzes the spatial spillover effects and dynamic evolution of agricultural carbon sinks in China under the dual-carbon goals. Using panel data from 30 provinces (2000-2022), it employs spatial econometric models (Spatial Durbin…
DatasetZenodo (CERN European Organization for Nuclear Research)2026#AI × ESGDOI
ML-Accelerated Quantum Variational Sampling for Carbon Capture Systems under Uncertainty
Jesús Pérez Expolio
This paper proposes a combination of machine learning and quantum variational sampling to optimize carbon capture systems under uncertainty. It applies AI/ML techniques to enhance CCUS process efficiency and cost reduction, promising indust…
Peer-reviewedJournalJournal for Research in Applied Sciences and Biotechnology2026#AI × ESGDOI
Optimizing Self-Compacting Concrete (SCC) Mix for Different Grades Using AI (ANN/RF models) for Low- Carbon Construction
Deepti Singh, Rakesh Kumar, Pooja
This study applies AI (ANN, RF, and GA) to optimize self-compacting concrete (SCC) mix designs, achieving 21–29% carbon emission reductions across grades M20–M60 while maintaining strength and workability. Using a dataset of 120 mixes, ANN …
Peer-reviewed🇨🇳 ChinaJournalSustainable Energy Technologies and Assessments2026#AI × ESGDOI
Carbon intensity and its associations with labor productivity and income inequality in China’s transition to carbon neutrality: A machine learning analysis of the energy sector
Mohaddeseh Azimi, Zhengfu Bian, Narges Salehi Shahrabi
This study uses machine learning to analyze the associations between carbon intensity, labor productivity, and income inequality in China's energy sector. It provides quantitative insights into how the decarbonization transition may affect …
Preprint🌍 GlobalCrossref2025#AI × ESGDOI
Green Intelligence Digital Twins: Climate-Resilient, Carbon-Aware Infrastructure
Murali Krishna Pasupuleti
This book proposes a framework for 'Green Intelligence Digital Twins' - computational models that integrate uncertainty quantification, causal inference, trustworthy machine learning, and lifecycle engineering to support climate-resilient, …
Peer-reviewedJournalZenodo (CERN European Organization for Nuclear Research)2026#AI × ESGDOI
THE ROLE OF ARTIFICIAL INTELLIGENCE IN CLIMATE CHANGE MITIGATION AND SUSTAINABLE DEVELOPMENT: A POLICY-ORIENTED ANALYSIS
Muazzam Mirjalolova
This paper provides a policy-oriented analysis of AI opportunities and challenges for climate mitigation and sustainable development, covering energy efficiency, environmental monitoring, and resource management. It emphasizes that effectiv…
PreprintCNEnvironmental Science & Technology2025#AI × ESGDOI
A Satellite-Driven Model for Monitoring Urban Material Metabolism, Embodied Emissions, and Carbonation
Yu Nie, Ting Mao, Yupeng Liu +3
This study uses machine learning on satellite imagery to reconstruct Xiamen, China's 30-year urban metabolism: building stock growth, material flows, embodied emissions, and cement carbonation offsetting 6.6% of lifecycle emissions. It achi…