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 14181–14200 of 36583 papers
Mei Xie, Zhuofan Yang, Yiyan Li +3
This review systematically synthesizes the application of Self-Determination Theory (SDT) to social acceptance of sustainable energy technologies. Following PRISMA, 34 studies (2000-2026) were analyzed, showing that autonomous motivation, s…
Rui Zhou
Using panel data from NICs (1990-2022), this study applies CS-ARDL and dynamic ARDL simulations to examine the energy transition-CO2 emissions nexus. It finds the EKC hypothesis invalid, while higher renewable energy shares yield long-term …
Jinqi Jiang, Zhijing Wu, guosen zhang +9
WaterMAP is a scalable ML framework for predicting GHG emissions from wastewater treatment plants. Using data from 5155 Chinese WWTPs, it estimates Scope 1/2/3 emissions and suggests 9.6-34.0% reduction potential by 2060.
Mengqi Yuan, Wenfei Zang, Guangchong Chen
Using provincial data from China (2012-2022), this study analyzes the coupling coordination between AI and high-quality energy development (AHCC). Both advanced, but AI lagged and regional disparities persisted, with intensifying spatial au…
万尧
This meta-analysis synthesizes quasi-experimental evidence on China's ETS and green innovation, using three-level meta-regression to disentangle design choices from real policy effects. It pre-specifies moderators and publication bias tests…
Wisdom Okere, Cosmas Ambe
This review integrates empirical research on climate-related financial disclosures (CRD) in the IFRS S1/S2 era, synthesizing findings on determinants, quality, and consequences. Applying multiple theories to studies from 2010-2025, it finds…
Tao Huang, Zhixin Liu, Chenyue Zhou
This paper analyzes the impact of the EU Carbon Border Adjustment Mechanism (CBAM) on corporate ESG scores, demonstrating that aggregate ESG scores fail to adequately capture carbon border shock risks. Using financial and emissions data of …
Maghfiratul Aini, Erna Chotidjah Suhatmi, Umi Hanifah
This study examines the impact of sustainability report disclosure and institutional ownership on firm value for Indonesian basic industry and chemical sector firms. Multiple regression analysis shows institutional ownership significantly a…
Federico Cammelli, Johan Six, Rachael Garrett
This study quantifies collusion in sustainability verification reports for cocoa supply chains, finding 25% collusion, reduced to 11% by withholding compliance thresholds. It underscores that monitoring and traceability alone are insufficie…
Michael Padget, Gregg Furie, Dionne Kringos +2
This paper is the first to systematically evaluate environmental sustainability measures for healthcare using quality measurement criteria. Six measures were assessed, and a minimum set of greenhouse gas emissions (scopes 1 and 2), water us…
Nan Deng, Xi Chen, Giovanna Michelon
This paper empirically investigates investor perceptions of mandatory sustainability reporting standards. Co-authored by researchers from the University of Bristol and the University of Padua, it analyzes how the adoption of such standards …
Congze Jiang, Kaiquan Wei, Xingfa Lai +4
A two-year field trial on the Loess Plateau showed that white film mulching combined with controlled-release urea (140 kg N/ha) maintained forage maize yield while reducing nitrogen input by 48% and cutting carbon, nitrogen, and water footp…
Mehrdad Taghipour, Sina Rostami, Muhammad Bilal
This scoping review systematically maps technologies and strategies to reduce energy use and carbon footprints in operating rooms, including HVAC optimization and AI-driven management. It identifies a methodological gap in kinetic energy ha…
Yajie Gao, Marja Roitto, Teng Hu +3
This study compares five farm-level carbon footprint tools for dairy production, revealing significant variability in total GHG emissions (415-913 t CO2eq/yr) due to differences in scopes and IPCC method tiers. Tool responsiveness to mitiga…
Meng Gao, Niko Heeren, Kai Gong +4
This paper examines the effects of supplementary cementitious materials (SCM) on freeze-thaw resistance and carbon footprint of blended cement concrete. SCM use reduces CO2 emissions from cement production but may affect durability. Provide…
Mareike Mauerer, T. Rocksch, Stefan Karlowsky +3
This study examines the impact of using nitrified urine fertilizer in hydroponic tomato cultivation on carbon footprint. It evaluates the potential for reducing greenhouse gas emissions by substituting chemical fertilizers, contributing to …
Thao Bich Thi Vu, Timo Ohnmacht, Bernadette Sütterlin +1
This paper investigates the relationship between teleworkers' attitudes (sceptical, pragmatic, innovative) and their commuting carbon footprints and subjective well-being. It aims to clarify how telework affects commuting emissions and how …
Rufaizal Che Mamat, Azuin Ramli, M. N. A. Ghani +3
This study compares fine tree regression and ANFIS for predicting carbon footprints across four stages of residential construction. Using 2000 observations, ANFIS outperformed Rtree in all stages, achieving lower RMSE values, especially in …
Jakob Unterkofler
This study examines how inequality in energy cost burdens relates to public support for climate policies in Europe, using Google Trends data. It finds that in countries without carbon pricing, higher inequality correlates with stronger supp…
Christian‐Oliver Ewald, Yaoyu Li
This study proposes a text-based framework for forecasting EU carbon prices, combining FinBERT sentiment analysis with PCA dimensionality reduction. Using weekly data from 2020-2024, the CNN-LSTM model with PCA inputs achieves the best perf…
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