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 9361–9380 of 28694 papers
Adrian Gheorghe Florea, Juma Hillary Wafula
This study analyzes the impact of climate misinformation on the allocation of climate funds across EU member states using panel data from 2014-2023. Combining econometric models, spatial analysis, and machine learning, it finds no statistic…
Renske Hijbeek
This paper explores how soil carbon affects crop yield constraints, suggesting that soil carbon management could contribute to agricultural productivity improvement.
Igor Matutinović, Djula Borozan
This study uses ridge regression on Chinese data (1990-2020) to assess the impact of energy and climate policies on CO2 emissions. Policy instruments contributed to mitigation but were not statistically significant overall; only market-base…
Shen Xiaowang
This paper proposes an energy transition pathway planning framework based on Prim-Lex Theory's eight-dimensional framework and the CLL phase-transition early warning model. It analyzes the current parallel expansion of fossil and renewable …
Md. Mahfuzur Rahman, Md. Anamul Hoque
This paper proposes an operational policy for production-delivery systems that minimizes carbon emission costs. By internalizing carbon emissions as a cost, it aims to balance operational efficiency and environmental impact. Specific method…
Laure Bouet, Marc Olivaux, Véronique Thireau +1
This study analyzes how local elected representatives in a French department adapt, negotiate, and reinterpret renewable energy projects, using resource dependence theory and dynamic capabilities. Based on 35 interviews, it finds that munic…
Pinto Anugrah, Rakibuzzaman Shah, N Mithulananthan +5
This study integrates LEAP and MCDA to prioritize renewable technologies for the BIMP interconnected power grid. Hydro shows the most balanced performance, while solar PV scores high but varies under economic conditions. Optimal portfolios …
Venkata Krishna Reddy, Aadam Quraishi, G. C. Prashant +1
This paper proposes a deep learning-based decision support system (DSS) for renewable energy (RE) investment and deployment. It uses CNNs to extract features from weather, energy, and economic data, RNNs to forecast energy demand and supply…
Andrzej Marciniak, Agnieszka Dudziak, Katarzyna Piotrowska +1
This study proposes a window-based analytical pipeline to identify operating regimes and their dynamic transitions in an integrated PV-building energy system, combining energy flow decomposition, sliding windows, and hidden Markov modeling.…
Dr. Unmana Sarangi
This paper reviews literature on environmental impact assessment (EIA) and sustainable projects in the Asia Pacific, highlighting roles of ADB and UNEP, and case studies in the Philippines, Indonesia, Nepal, etc. It concludes that robust EI…
Kathirvel Ayyaswamy, Naren Kathirvel
This paper examines the role of electric vehicles (EVs) in fostering a circular economy in India, focusing on battery recycling, component life cycles, and reducing fossil fuel dependence. It analyzes government policies, subsidies, and inf…
Gregor Murray, Mathieu Dupuis, Julie Hagan +2
This introduction to a thematic issue explores how workers and unions act on climate change. It synthesizes seven studies, highlighting the role of unionization and collective bargaining, diverse strategies, gender impacts, and the challeng…
Bożena Horbaczewska
This article traces the evolution of energy in economic thought from pre-classical to modern times, advocating a shift from mechanistic-deterministic models to holistic frameworks incorporating thermodynamics and entropy. It concludes that …
Saqib Munir, Mushab Rashid, Abdul Ghaffar +1
This paper analyzes how international aid, domestic governance, and geopolitical risk condition the momentum of energy transitions in Global South countries. It offers implications for designing decarbonization policies in developing nation…
S Kumar, Y. Lalitha Kameswari, Th Basanta +2
This chapter discusses the importance of energy storage for integrating renewable energy, covering technologies like flywheels, batteries, thermal storage, pumped hydro, and supercapacitors. It emphasizes their role in grid management, load…
Lila Simon, Abino Simon, Aalbin Simon
This chapter explores the integration of AI and renewable energy for a sustainable energy ecosystem. It reviews the renewable landscape in India and globally, detailing AI applications in solar, wind, hydro, biomass, and geothermal, includi…
PhD Yuel Okey Kalu, Richard C. Udeala, Sunday Uta Kalu
This study surveys builders and civil engineers in South-East Nigeria on the optimization of building-integrated renewable energy systems (BIRES). It finds low adoption and awareness, with barriers including lack of design guidelines, high …
Zhaoyang Xu, Lei Zhu, KuoRay Mao +1
This study analyzes three solar projects in China (Ningxia, Shandong, Jiangsu) to examine how low-carbon transitions affect energy justice (distributive, procedural, recognition). Using field interviews and policy analysis, it develops a fo…
Michaela Makešová, Michaela Valentová, Matouš Pilnáček
This paper uses latent class analysis to develop a typology of household photovoltaic (PV) investors, revealing heterogeneity in investment behavior. Based on Czech data, it identifies distinct classes of investors by characteristics and mo…
Ravi Sheth, Chandresh Parekha
This chapter examines the synergy between renewable energy and AI, highlighting how AI technologies like machine learning and deep learning can optimize solar and wind energy systems through predictive analytics, demand forecasting, and rea…
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