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 18261–18280 of 31467 papers
Petra Minnerop, Friederike E. L. Otto
This paper analyzes the landmark 2025 Lliuya v. RWE judgment in Germany, where the court confirmed the applicability of German nuisance law to transnational climate claims. It examines the court's handling of scientific evidence on 'imminen…
Mirel Alvarez, Miriam Lourdes Filgueiras Sainz de Rozas, Anaely Saunders +1
This paper proposes a management model for international cooperation to develop renewable energy in Cuba. It uses a structured questionnaire with 7 dimensions, 22 activities, and 5 subprocesses, validated through expert evaluation and stati…
Antonio Cavallin Toscani, Vishal Agrawal, Atalay Atasu +1
This paper addresses imperfect displacement in life cycle assessment for refurbishing and remanufacturing by endogenizing the displacement rate using operations management models. A case study in electronics shows that geography significant…
Müller, Leander Amadeus, Luck, Nathalie, Watson, Jim +2
This paper analyzes the impact of socio-political scenarios on the cost of capital for green hydrogen projects, using Ukraine as a case study under deep uncertainty, highlighting challenges for transition finance in volatile regions.
Saad, Okwiri Minado, Murimi, Michael Kairu
This retrospective study evaluates solar water pumping in Kenya's Kajiado region over 10 years. It finds 60-75% cost reduction vs diesel, but notes that zero marginal cost of solar incentivizes over-pumping, accelerating aquifer depletion. …
Mutule, Anna, Zalostiba, Diana, Baltputnis, Kārlis +1
This dataset provides aggregated hourly electrical load and generation profiles for the Kurzeme region of Latvia for 2025, based on measurements from 17 substations. It includes active/reactive power for both load and generation, covering 1…
Zhuravlova, Inna, Kaltenegger, Sarah, Vera, Constanza
This handbook compiles insights from surveys, interviews, and workshops on CCUS adoption in municipalities. It features best practices from front-runner cities, cost calculations, and funding opportunities to help municipalities achieve net…
Ranjan Kumar Das, Dr. Ramjee Singh
This paper provides a comprehensive review of India's approach to sustainable development, covering its policy framework, government initiatives like the National Action Plan on Climate Change and National Solar Mission, and commitment to n…
Wang, Yushu, Du, Wenli, Yang, Minglei +1
This study develops a spatial-temporal optimization model for China's cement industry (2025-2060) incorporating provincial resource heterogeneity and cross-province logistics. It evaluates cost-effective decarbonization pathways using techn…
Anonymous
This study examines the spatial mismatch between public EV charging supply and travel-derived decarbonization opportunity across 1,494 grid cells in central Shanghai. It employs 2SFCA accessibility, bivariate LISA, GeoShapley-style attribut…
Ruiqiao Song, Renjie Sun
This paper explains the role of fintech in enhancing green finance by reducing costs, increasing financial inclusion, and improving information. It reviews the incorporation of technology such as blockchain and AI into green finance, coveri…
Massimo Gagliardi, A. Di Lullo, Donatella Stocchi
This paper presents Eni's Delta-Climate methodology, which assesses the resilience of industrial assets to climate change by quantitatively verifying the consistency of design bases with projected future climate conditions. It sets toleranc…
Feride Çiğdem Kara Dülger, Merve Tuna Kayılı
This study conducts a life cycle assessment of Turkey's first Passive House-certified building, the Gaziantep Ecological House, evaluating trade-offs between embodied carbon and operational energy efficiency for various wall materials. Bric…
Asad S. Albostami, Amer A. Hijazi, Saif Alzabeebee +2
This study develops machine learning models (XGBoost, GEP, etc.) to predict compressive strength of eco-friendly concrete using waste glass powder (WGP) as partial cement replacement. A database of 230 records was compiled, with 3% WGP achi…
Abdeliazim Mustafa, B. Tayeh, A. M. Mohamed
This review examines 61 articles on integrating LCA and CE in buildings. It finds a shift toward dynamic and parametric LCA, with CE strategies generally beneficial but context-dependent. Challenges include methodological assumptions, data …
Majdi Argoubi, Khaled Mili
Proposes a fuzzy multi-objective optimization model for designing a reverse logistics network for end-of-life EV batteries in Saudi Arabia. The model balances economic and environmental costs under uncertainty. A case study in Riyadh shows …
Qingzi Gu, Babatunde Sunday Eweade, Cathrine Banga +1
This study examines the impact of institutional quality on renewable energy consumption in the US using wavelet quantile regression with quarterly data from 1990 to 2024. It finds that economic growth, FDI, and trade openness positively inf…
Tianyu Zhuo, Xue-Yi You, Lixin He +12
This study demonstrates that stratification in reservoirs enhances carbon sequestration by promoting microbial necromass accumulation, but also imposes a self-limiting effect that caps total sequestration. The findings contribute to underst…
Claudia Masselli, Sabrina Gargiulo, Vincenzo Orabona +3
This numerical study evaluates the energy performance enhancement from single-effect to multicaloric solid-state heat pumps, demonstrating potential carbon footprint reduction.
Ram Chandra Chaurasia Ram Chandra Chaurasia, Rajshekhar Singh Rajshekhar Singh
This study proposes an AI-IoT framework for real-time methane monitoring, prediction, and carbon footprint reduction in underground coal mines. Using LSTM, random forest, and reinforcement learning, it achieves over 93% prediction accuracy …
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