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.
Showing 261–280 of 1414 papers
Xiaobin Wang, Yuning Jiang, Zhihua Zhang +4
This paper proposes a contextual information-based distributionally robust optimization method for decarbonizing oil and gas field power systems. It integrates renewable energy while managing uncertainty, aiming to reduce operational costs …
Fan Zhang, Bo Wen, Ditao Niu +4
This study integrates life-cycle carbon accounting, statistical analysis, Monte Carlo simulation, and machine learning to assess embodied carbon in RC buildings. Using data from 124 buildings in Shaanxi Province, it finds material productio…
Murali Krishna Pasupuleti
This monograph presents an integrated research architecture for planetary resilience, combining Earth-system AI, ClimateTech modeling, and sustainable energy intelligence. It covers uncertainty-aware design, physics-guided ML, MLOps, and se…
Ömer Algorabi, Ersin Namlı
This study compares deep learning (GRU) and boosting models for forecasting electricity generation in Türkiye and Germany, then evaluates 2030 BAU, ST, and EC scenarios. GRU performs best for Türkiye, boosting for Germany. Scenario analysis…
Xie M.
This paper empirically analyzes the impact of green finance and financial technology on regional green energy technological innovation using dual machine learning and spatial econometric models. It reveals the effects of financial policy an…
Mejda T.
This paper analyzes the causal impact of regtech adoption on corporate greenwashing using staggered DiD, DDD, and generalized random forests. It explores heterogeneous effects across firms, contributing to the AI×ESG intersection by applyin…
Annu Dhull, D. Abdukhamidov, D. Yusupov +3
This paper proposes a digital twin framework for real-time monitoring and performance optimization of green hydrogen electrolysers. It combines physics-based models with AI prediction to enhance efficiency and stability under fluctuating re…
Yang Lu, Joston Gary
This study develops an environmental systems engineering framework for carbon-management decision support in prefabricated construction, integrating production and transport decisions under dynamic energy prices and carbon signals. A tri-ob…
Yuzhi Wang, Cong Zhang
This study analyzes the causal effect of China's intellectual property pilot policy on low-carbon green energy eco-co-evolution (LCEE) using spatial Durbin DID and double machine learning. The inclusive potential of regional innovation ecos…
Junhao Ren, Honglin Gao, Sijie Wang +5
This paper proposes a multi-agent reinforcement learning approach to jointly design a low-carbon peer-to-peer (P2P) energy market and bidding strategies in microgrids. It optimizes economic and environmental outcomes, promoting renewable in…
Will Alpine, Nathan B. Geldner, Holly Alpine +1
This study models AI as a bidirectional productivity amplifier in a global CGE model, finding that AI-driven productivity gains in fossil fuel sectors lead to net CO2 emission increases of 0.47-1.8 Gt annually, outweighing reductions from r…
Joseph Sanderson
Climate change intensifies food safety risks; digital technologies (AI/ML, IoT, blockchain) strengthen risk analysis via monitoring, prediction, and traceability. Three case studies (AI sorting, blockchain supply chain, IoT cold chain) show…
Youbi D.
This paper systematically reviews the literature on AI applications in sustainable finance, mapping current research and identifying emerging paths. It analyzes AI's impact on ESG assessment, climate-related disclosure, and investment decis…
Gupta U.
This paper proposes a green procurement policy for AI labs' compute resources, requiring minimum environmental disclosures, energy metering, and emission reduction targets. It addresses the growing energy consumption of AI computing and pro…
Vijeta, Neha Yadav, Meenakshi Rao
This conceptual study proposes integrating forensic accounting into sustainability reporting to enhance credibility and stakeholder trust. It addresses greenwashing and weak assurance by applying forensic techniques and emerging technologie…
Vijeta, Neha Yadav, Meenakshi Rao
This conceptual study proposes a framework integrating forensic accounting into sustainability reporting to enhance credibility and stakeholder trust. It addresses greenwashing and selective disclosure by applying techniques like fraud risk…
Shi Yang, Polina Ellina, Kyriakos Christofi +2
This study develops an ESG disclosure quality evaluation framework tailored to the agricultural chemicals industry, based on GRI 2021 Standards and Chinese regulatory requirements. Using qualitative content analysis and AHP, it constructs a…
Lu Gong
This study analyzes how digital monitoring and ESG disclosure affect the assetization efficiency of agricultural carbon sinks. Using data from typical agricultural regions, it demonstrates that high-quality monitoring and ESG disclosure sig…
Ammar Ali Gull, Irfan Haider Shakri, Faizul Haque +1
This study examines the impact of external sustainability assurance and Big-4 providers on GHG emissions using a global sample of 7,968 firm-year observations from 34 countries. It finds a negative association, stronger in stakeholder-orien…
Yu Qiao, Xinwen Deng, Xiaoying Huang +7
This study proposes a UAV-UGV collaborative delivery framework for urban last-mile logistics, developing a multi-objective optimization model considering efficiency, safety, and low-carbon performance. A visual simulation platform using HTM…
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