GX Research Hub · English
GX & Decarbonization Research
This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing 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🌍 GlobalJournalEco Cities2026#AI × ESGDOI
Circular economy and sustainable business models in the energy sector: a scoping review of digital transformation, AI integration, and sustainability strategies
Shankar Subramanian Iyer, Dr Brinitha Raji, Dr. Rajesh Arora +1
This scoping review examines the integration of circular economy (CE) and AI/digital technologies in the energy sector, combining 143 peer-reviewed sources with interviews of 15 industry leaders. It finds that CE offers significant value bu…
Preprint🇪🇺 EuropeZenodo2026#AI × ESGDOI
Carbon pricing is the cornerstone of European climate policy, yet its evaluation remains trapped in an average-effects paradigm. The most comprehensive meta-analysis to date, covering 80 ex-post evaluations across 21 carbon pricing schemes, establishes that carbon pricing reduces emissions by 5% to 21% in the first years of operation, but also documents that heterogeneity in outcomes is driven by policy design and context rather than by price levels or instrument type (Döbbeling-Hildebrandt e...
LEKBIR, DJAMEL
This study develops an Estimation-to-Compensation framework using double/debiased machine learning and causal forests to estimate installation-level heterogeneous effects of the EU ETS on ~1,900 German installations, validated on Chinese pi…
🌍 GlobalDatasetZenodo2026#AI × ESGDOI
Coded evidence-map dataset and reproducibility package for "From Carbon Prediction to Integrated Carbon Decision Support: A PRISMA-Informed Evidence Map of AI and Computational Methods in the Built Environment"
Mohammadi, Sepehr, Mostafa, Sherif, Jadidi, Zahra
This is a coded dataset and reproducibility package for a PRISMA-informed evidence map of AI and computational methods for carbon decision support in the built environment. It includes a 457-record audited database (335 primary studies, 102…
Peer-reviewedConferenceSPE Nigeria Annual International Conference and Exhibition2026#AI × ESGDOI
Data-Driven Greenhouse Gas (GHG) Accounting Software for Nigeria's Oil and Gas Sector
E. P. Egbe, E. O. Diemuodeke, E. G. Udonkwo +1
This paper develops a data-driven GHG accounting software for Nigeria's oil and gas sector, automating Scope 1 and 2 emissions estimation based on the API Compendium. It addresses manual, fragmented practices by integrating operational and …
Peer-reviewed🇨🇳 ChinaJournalEnergy Economics2026#AI × ESGDOI
Artificial intelligence and the energy trilemma: A general-purpose technology perspective
Eduardo Andres Pardo-Piñashca, Muhammad Shahbaz, Ioannis Kyriakou +1
This paper examines AI as a general-purpose technology and its impact on the energy trilemma (security, equity, sustainability). It discusses AI's transformative role in optimizing energy systems and informing policy, offering insights for …
PreprintZenodo (CERN European Organization for Nuclear Research)2026#AI × ESGDOI
Smart Plantation Strategies for Pollution Mitigation and Climate Resilience: A Review of Emerging Technologies and Nature-Based Solutions
Kashaf
This review outlines smart plantation as a nature-based solution integrating strategic vegetation placement with digital technologies (AI, sensors, remote sensing) to reduce air pollutants, store carbon, and improve urban microclimates. It …
🇪🇺 EuropeJournalCESifo2026#AI × ESGDOI
Unpacking the Distributional Implications of the Energy Crisis: Lessons from the Iberian Electricity Market
Natalia Fabra, Clément Leblanc, Mateus Souza
This study quantifies the distributional impacts of the Iberian solution, a wholesale electricity market intervention in Spain and Portugal during the 2021-2023 European energy crisis, using machine learning and market simulations. The cris…
🌍 GlobalConferenceSPE/IADC Asia Pacific Drilling Technology Conference and Exhibition2026#AI × ESGDOI
Operationalizing Emission Management: A Drilling Rig Company Transformation Journey
A. Wesley, T. Kangwansura
This paper reports a drilling contractor's transformation from annual sustainability disclosure to an operational, AI-enabled emission management system. Based on a 2021 GHG baseline, operational control boundaries, and Net Zero 2050 commit…
Peer-reviewedJournalMathematics2026#AI × ESGDOI
An Adjustable Robust Approach for ESG-Aware Portfolio Optimization Under Decision-Dependent Return Uncertainty
Futi Liu, Zian Zhao
This paper addresses ESG-aware portfolio optimization under decision-dependent return uncertainty. It constructs a joint polyhedral uncertainty set and formulates a two-stage robust optimization with CVaR constraints, solved via column-and-…
Peer-reviewedJournalEKUITAS (Jurnal Ekonomi dan Keuangan)2026#AI × ESGDOI
CYBER-AUDITING THE FUTURE: HOW CONCEPTUAL FOUNDATION OF DIGITAL ASSURANCE REDEFINES RISK, ACCOUNTABILITY, AND TRANSPARENCY IN MULTINATIONAL FIRMS
Idham Idham, Chusnul Rofiah
This study examines how cyber-auditing and the conceptual foundation of digital assurance redefine auditors' roles in multinational firms. Using a systematic literature review, it finds that integrating AI and data analytics into audit prac…
Peer-reviewedCNJournalChina Accounting and Finance Review2026#AI × ESGDOI
Exposure to water risk and firm valuation: evidence from geographic proximity to cancer villages
Yingwen Guo, Miao He, Weiyin Zhang
This study examines the impact of geographic proximity to cancer villages on firm valuation using Chinese listed firms from 2004 to 2022. A one-standard-deviation increase in proximity reduces Tobin's Q by about 1.7%, driven by higher compl…
Peer-reviewedJournalSustainability2026#AI × ESGDOI
Sustainable Autoclaved Aerated Concrete Production Strategies Using a Hybrid Discrete-Event Simulation and Machine-Learning Surrogate Framework
S. Amoo, Ali Attajer, Ismahen Zaid +1
This study develops an optimization framework for sustainable AAC production using discrete-event simulation and machine-learning surrogates. It generates 116,640 production scenarios and trains ML models to predict CO2e emissions, cost, an…
Peer-reviewed🌍 GlobalJournalSustainability2026#AI × ESGDOI
An AIS–MRV Consistency-Enhanced Dynamic Network Framework for Shipping Traffic Resilience Assessment and Disruption Recovery Characterization
Ruolan Zhang, Wei Shen, Dejian Wei +2
This paper proposes a dynamic network framework integrating AIS and MRV data to assess shipping traffic resilience and green operations. Using real AIS and full-year DGX data, it computes functionality curves and Resilience-Green Index valu…
ConferenceSPE/IADC Asia Pacific Drilling Technology Conference and Exhibition2026#AI × ESGDOI
Carbon Integrity Intelligence: An AI-Driven Framework for Dynamic Regional Governance and High-Fidelity CCUS Operations
K. Sonawane, P. Saini, U. Biradar +3
This paper proposes an AI-driven integrated digital framework for CCUS to enhance containment assurance and carbon credit credibility. It integrates multi-modal data (DAS/DTS, microseismic, satellite) and uses anomaly detection, Bayesian in…
Peer-reviewedCNJournalSustainability2026#AI × ESGDOI
Green Finance, Infrastructure Upgrading, and Urban Supply Chain Resilience: Evidence from China’s Green Finance Reform and Innovation Pilot Zones
Yilin Wang, Xujing Dai, Xueyan Li
This study examines whether China's Green Finance Reform and Innovation Pilot Zones (GFRIZ) policy improved urban supply chain resilience, using panel data for 285 cities from 2012-2024 and a partially linear Double Machine Learning approac…
Proceedings of International University Travnik2026#AI × ESGDOI
PRIMJENA UMJETNE INTELIGENCIJE U RAZVOJU ENERGETSKO- EFIKASNIH PAMETNIH RASKRSNICA I PAMETNIH GRADOVA ZASNOVANIH NA OBNOVLJIVIM IZVORIMA ENERGIJE / APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF ENERGY-EFFICIENT SMART INTERSECTIONS AND SMART CITIES BASED ON RENEWABLE ENERGY SOURCES
Nehad Gaši, Kemal Spahić, Bekir Fulan
This paper applies AI to optimize smart intersections powered by renewable energy, using machine learning on traffic, energy, and weather data for dynamic signal control. It reduces congestion, improves safety, and cuts CO₂ emissions, contr…
Peer-reviewed🇨🇳 ChinaJournalEnergy Conversion and Management X2026#AI × ESGDOI
Simulation-based smart emission reduction and energy security using renewable energy bonds, AI-green bonds, and incentive mechanisms
Bo Zhao, Jafar Hussain, Zhenyu Qiu +2
This study analyzes the impact of adopting Smart Emission Control Systems and Energy Security on CO2 reduction and profitability in a supply chain of 500 manufacturers, agents, and retailers using game theory and simulation-based optimizati…
Peer-reviewed🇨🇳 ChinaJournalScientific Reports2026#AI × ESGDOI
Assessment and pathways of the energy production revolution in the Yellow River Basin, China towards carbon peaking: a machine learning approach
Jian Xu, Jie Song, Yifan Yan +3
This study constructs an energy production revolution index (EIT) for the Yellow River Basin and uses stacking ensemble and Lasso-STIRPAT models to project carbon emissions and EIT from 2025-2045. Scenario analysis reveals optimal pathways …
Peer-reviewed🇨🇳 ChinaJournalSustainability2026#AI × ESGDOI
How Do Pilot Policies for Climate—Adaptive City Development Enhance Urban Green Energy Efficiency?
Chuanchao Li, Yuanhe Du, Shuangyang Zhai
Using data from 284 Chinese cities (2012-2023) and a quasi-natural experiment of climate-resilient city pilots, this study applies double machine learning and spatial lag models to show that climate risk governance significantly enhances ur…
Journal2026#AI × ESGDOI
Dynamic monitoring and evaluation of full-chain carbon footprint of smart cold chain integrating IoT and machine learning
Xiao Zhang, Zhaoqiao Ding
This paper proposes a smart cold chain system integrating IoT sensors and machine learning to enable dynamic monitoring and evaluation of full-chain carbon footprint. Real-time data collection and predictive models optimize energy consumpti…
