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 381–400 of 4285 papers
Hughes, Hunter
Frames the clean energy transition as an institutional crisis of state capacity, arguing for a modernized Developmental State with coordinated planning, strategic finance, and industrial discipline. Offers a 12-chapter architecture and a 20…
MOUSSAFIR Hasna
This paper proposes a unified conceptual framework to model how the CSRD and ESRS reshape corporate disclosure through double materiality. Integrating signaling, agency, legitimacy, and stakeholder theories, it argues that structural conver…
Frederik, Fristed
This dataset supports a study analyzing the roles of renewable fuels and CCS in net-zero transport and energy systems. It provides input data and results for 37 scenarios using the Balmorel energy system model. Open-source model and data en…
Sikder, Pranta
GETP v1.0 is a harmonized database of realized ascent and descent rates for electricity technologies across 214 countries (1985-2025). It applies a symmetric diagnostic engine to both expanding and contracting trajectories, enabling compari…
Sikder, Pranta
An open panel of marginal emission factors for electricity across 203 economies (1999-2025), enabling accurate assessment of emissions from additional electricity demand (EVs, heat pumps, data centers). It provides average, operating margin…
Yuanyuan Ma, Siyu Peng, Yun Yu
This study develops a hybrid forecasting framework integrating CEEMDAN, sample entropy reconstruction, and coefficient of variation ensemble to capture multi-scale nonlinear carbon price dynamics. SHAP and TVP-SV-VAR reveal scale-specific a…
Sheng Zhao, Jingran Zhang, Jinyang Lu +6
This study compares four routes for green methanol production from biomass and renewable power, revealing trade-offs in carbon use, energy efficiency, emissions, and cost. Hydrogen-integrated gasification achieves 92% carbon utilization and…
Bowen Tian, Pei Zhao, Min Liu +11
This study analyzes the interaction between V2G and time-of-use pricing using a unit commitment model of the 2030 Jing-Jin-Tang grid with Bayesian optimization. It finds that current static tariffs incentivize EV discharge during midday sol…
Ma, Minghui, Valdiserri, Paolo, Ballerini, Vincenzo +2
This study proposes a deep learning framework to predict building heat load for a single apartment in Bologna using previous 24h data. Optuna optimizes hyperparameters for LSTM, TCN, MLP, XGBoost, and LR; LSTM performs best. Physics-constra…
Luh, Sandro (author), Kannan, Ramachandran (author), McKenna, Russell (author) +2
This study extends the Swiss TIMES energy system model with heterogeneous consumer segments and charging infrastructure (CI) options to analyze BEV adoption and net-zero implications. Results show BEV share reaches 39-77% by 2050, requiring…
Luh, Sandro (author), Kannan, Ramachandran (author), McKenna, Russell (author) +2
This study integrates travel time duration and valuation into the Swiss TIMES Energy System Model (STEM) to quantify modal shifts in passenger transport. Results show that speed changes on medium and long trips (e.g., highway speed limits, …
Liu H.
This paper empirically analyzes how regulatory environments influence green bond issuance among active OECD issuers, suggesting that stronger policy frameworks may boost issuance volumes and market participation.
Sohail M.
This paper empirically examines how AI adoption affects ESG performance in the German banking sector, focusing on the mediating role of green finance. It suggests that AI can enhance banks' ESG assessments and promote green lending.
P. Bryant, J. Hondros
This article reviews environmental radiological impacts across the nuclear fuel cycle, from mining to decommissioning and waste management. It argues that over-application of the ALARA principle leads to resource misallocation and distorted…
T. Saji, George Paul, M. Nagalingam
Using US data from 1990-2023 and a NARDL model, this study reveals asymmetric impacts on renewable energy consumption. Positive energy innovation shocks boost consumption, but negative shocks have nearly twice the adverse effect. Green fina…
Xiaoxiao Tan, Xiangyang Xu, Hao Liu
This study forecasts demand for lithium, cobalt, nickel, and manganese for China's new energy batteries from 2010 to 2060 using dynamic material flow analysis and scenario analysis. Demand is projected to rise significantly by 2060, with li…
Jingyan Yang, Shangheng Yao, Chaojun Li +4
A spatiotemporal life cycle assessment quantifies wind power's carbon mitigation benefits. Historical net mitigation reached 3,690 Mt CO2e (2014-2023), with emissions at 8.5% of direct displacement benefits. Climate-priority deployment coul…
Xuelong Zhang, Xiaoling He, Mei Li +3
Using panel data of Chinese listed energy firms (2010-2023), this study shows AI adoption significantly reduces carbon emission intensity. Executive digital background strengthens the effect, and low-carbon city pilots provide complementary…
Yizhi Guan
This study compares ESG disclosure quality between 10 traditional energy and 34 new energy companies using content analysis. New energy firms adopt more frameworks, achieve higher MSCI ratings, and include Scope 3 in net-zero commitments mo…
YunWei Shen
Using panel data of Chinese A-share listed firms from 2011 to 2023, this study finds that ESG disclosure significantly reduces stock price synchronicity, with stronger effects in non-manufacturing and state-owned enterprises. Environmental …
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