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 1841–1860 of 4137 papers
Jiayuan Guo, Kai Quan Zhang, Yanlai Wang +1
This study integrates XGBoost with SHAP interpretability to identify carbon emission drivers of agricultural exports using panel data from Central China (1993-2019). The optimized model achieves high predictive accuracy (R²=0.935), revealin…
Yi Zhou, Jian Han, Yang Qu +6
This study analyzes challenges to maintaining electricity supply security during China's transition from fossil fuels to high-penetration variable renewable energy (VRE). Using Causal Loop Diagram (CLD) method, it identifies dynamic feedbac…
Yan-Chen Gu, Lian-Hong Lü, Nan Zhang
Using World Bank and IEA data (1970-2023), this study applies MK test, Tapio decoupling, and LMDI decomposition to assess carbon peaking across 218 countries and analyze drivers in China and six developed nations. By 2023, 57 countries peak…
K Sivasankar*
This study proposes a real-time coordination control strategy for solar PV and diesel generators during grid outages, enabling high solar penetration while maintaining stability. Simulations show reduced diesel fuel consumption and carbon e…
Nazia Bhimani, Zahra Al Sulaimi, Dua Al Shibani +1
This paper presents the design, lab evaluation, and field implementation of a reduced-Portland cement system for well cementing, substituting 37% of Portland cement with SCMs. In a large-scale drilling project in Oman, this achieved ~130 to…
Sonia Sayari, Nidhal Mgadmi, Majed A Helmi, Hanen Louati, Abdulaziz M Basahel, Hamed Yousef Alshinkity, Sumayya Albalawi
Using US data from 1990-2024, this study examines how green economy, FinTech, and governance affect environmental sustainability. Applying cointegration, error-correction, QVAR, and heatmap diagnostics, it finds that renewable energy, fores…
Yu Hongyuan
This paper analyzes how the global shift from fossil fuels to an electricity-centered energy order reshapes geopolitical structures. Unlike the oil age, competition now centers on critical minerals, power equipment, nuclear technology, and …
Brown, Patrick, Carag, Vincent, Chen, Yunzhi +19
ReEDS 2.0 is a capacity planning model simulating the evolution of the U.S. bulk power system through 2050. It is widely used for analyzing renewable deployment and decarbonization pathways, providing critical insights for policy and indust…
Xia-Bauer, Chun, Hermwille, Lukas, Leipprand, Anna
China and Germany's low-carbon steel labels are technically comparable, supporting deep decarbonization and renewable-powered scrap production. Differences in system boundaries and accounting methods remain; greater alignment could improve …
Maria Aluchna, Leszek Bohdanowicz, Bogumił Kamiński
This study examines how female board representation affects the scope of climate-related disclosure (energy use and GHG emissions) after mandatory NFRD reporting. Using a difference-in-differences design on 72 Warsaw Stock Exchange firms, i…
Zhifan Liu, Danlin Hou, Yang Li
This study systematically analyzes the CO2 reduction potential of low-carbon materials and passive design strategies for a typical single-family house in Vancouver, Canada. CLT is the most effective substitute, and combining optimal materia…
Nikolaos Skordoulias, Sotiriοs Karellas, Dimitrios V. Lyridis +2
This study proposes an integrated optimization framework for dynamic operation of pressurized alkaline electrolysers powered by hybrid solar-wind PPAs. A multi-state module-level model with MINLP constraints minimizes operating costs. Appli…
Yangjun Zeng, Huayan Geng, Yiwei Qiu +6
This paper proposes a hierarchical carbon-driven incentive mechanism (PCIM) integrating carbon policy with multi-energy market interactions for renewable power-to-ammonia (ReP2A) production. A two-layer trading framework models competition …
Xiaoyu Guo, Weisen Wang, Zhanghua Xu +6
This study develops a UAV-LiDAR and machine learning framework for organ-level aboveground carbon (AGC) estimation in bamboo forests. XGBoost and Random Forest achieved highest accuracy (stem R2=0.82, leaf R2=0.73), offering a cost-effectiv…
Yue Wang, Xinyi Zhao, Guohao Sun +3
Analyzing measured data from 530 public building retrofit projects across 11 Chinese provinces, this study quantifies realized energy savings and cost-effectiveness. Mean energy use intensity decreased by 19.1%, with 99.2% of projects achie…
Emily Preedy, Darren L. Oatley-Radcliffe, Jose Gayo Pelaez +3
This study demonstrates a commercial-scale tubular photobioreactor using CO2 from a nickel refinery to grow microalgae, achieving biomass productivity of 0.11 g/L/d and sequestering ~1 tonne CO2/year. Techno-economic analysis shows positive…
MORELLI, Rocco
This paper critically revisits the Marchetti-Nakicenovic logistic substitution model of energy sources (IIASA, 1979) against actual global energy mix data for 2024-2025. It finds major divergences due to geopolitics and technological accele…
M. Natili, Alessandro Pellegata, Francesco Visconti
Amid the energy crisis after the Ukraine invasion, this conjoint experiment reveals European citizens' preferences for policy packages balancing climate, energy security, and income. Support for renewables rises with social transfers and pr…
Huazhe Jiao, Yongze Yang, Yixuan Yang +7
This review provides a theoretical and practical foundation for using red mud (RM) as a supplementary cementitious material. It clarifies CO2 mineralization pretreatment, interfacial bonding mechanisms, and alkali-activation pathways, demon…
Md Ruhul Amin, Sharif Mazumder, Pritam Saha
Using a novel climate policy uncertainty (CPU) measure, this study shows that firms reduce future innovation (patents, citations, value) in response to climate policy risk, with green innovation less affected. The mechanism is a precautiona…
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