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 1461–1480 of 5783 papers
Leonard Terver Thomas
This study analyzes the impact of the Strait of Hormuz crisis on global trade, focusing on route diversion and economic consequences. It finds a loss of over 250 million barrels of oil supply, a surge in crude oil prices exceeding 60%, and …
Thanh Phuc Nguyen, Trang Thi Kieu Duong, Thi Nha Truc Phan
This study analyzes the asymmetric impacts of renewable energy, bank credit, and industrial robots on environmental sustainability (ecological footprint and GHG emissions) in the top five robot-installing countries (2011-2023) using panel q…
Chengjiang Li, Xiu Gu, Quande Qin +4
This study integrates dynamic life cycle assessment with system dynamics to evaluate 13 alternative marine fuels (e.g., ammonia, methanol, hydrogen, soybean biodiesel) for the Asia–Europe Green Shipping Corridor through 2050. Considering te…
C. Turhan, G. Durmuş, Mehmet Furkan Özbey +2
This study proposes a life-cycle carbon assessment framework for educational buildings, simulating seven retrofit scenarios for university buildings in Italy and Turkey. Psychological-adaptive HVAC control is most effective, achieving ~19.3…
Dorsa Razeghi-Jahromi, Goran Strbac, H. Ameli
This study develops a scenario-based ML framework to project UK electricity and gas demand to 2050 under climate forcing pathways (RCP2.6, 4.5, 8.5) and net-zero assumptions. By 2050, electricity demand under RCP8.5 is 4.1% higher than RCP2…
Paul Tautorat, Darius Sultani, Natalija Ljubic +3
This study develops a real options valuation model to analyze decarbonization investments in 179 EU cement plants under uncertainties in allowance prices, CCS costs, and CO2 infrastructure. Results show that uncertainty perception strongly …
Wen Yi, Nikita Strelkovskii, Tingkun He +8
This paper projects black carbon emissions and climate impacts from expanded Arctic transit shipping through 2050. It quantifies how cost-driven shipping shifts could increase short-term climate forcing, highlighting the need for policy int…
Randy Ramadhar Singh
This review analyzes Trinidad and Tobago's hydrocarbon history through energy justice, examining four events using distributional, procedural, and recognition justice. It finds a degraded extractive social contract and proposes participator…
Yisong Zhu, Wencheng Ma, Yu Ouyang +4
This paper examines the management and reshaping of urban water supply systems from the perspective of carbon emission reduction. While specific methods and results are unavailable, it focuses on the potential for reducing energy consumptio…
Meiling Zhao, Paul Upham
This study compares national sociotechnical imaginaries underlying solar PV policies in China, Germany, the Netherlands, and Spain using social representations theory. It finds common themes like energy security and decarbonization, but dif…
Ruxue Du, Han Han, Gege Yin +3
This Perspective proposes a next-generation building heating system integrating renewable energy-driven heat pumps with synergistic thermal and electrical energy storage. Techno-economic modeling reveals the superiority of combined TES-EES …
Huang Qunchao
This conceptual paper examines ethical tensions in renewable energy transitions, focusing on end-of-life material risks from PV, wind blades, and batteries. Drawing on Jonas, Rawls, and Gardiner, it argues for 'bounded acceleration' linking…
Sobia Naseem
This study examines the asymmetric effects of ICT, renewable energy, FDI, and economic growth on CO2 emissions in G-20 countries from 2000 to 2022 using DOLS and PMG-ARDL. Findings show that FDI, growth, and ICT increase emissions, while re…
Boyuan Wang, Zhifeng Sun, Yongzhi Zhou +5
This study addresses the benefit divergence between overall system and PV utilization under high-proportion building PV, proposing a framework with carbon constraints and grid absorption costs. Using a Beijing retrofit office, it compares t…
Zhangsen Dong, Xiao Li, Ruixin Xu +2
This study develops an integrated framework combining emission inventories, LEAP scenario modeling, and charging demand estimation for Zhengzhou's road transport. Under the dual carbon scenario, CO2 peaks in 2030 at 36 Mt, 20% below the exi…
Jingcheng Li, Tianyang Wang, Menggang Li +1
This study analyzes the effect of green finance on China's electricity sector, finding that while it curbs direct carbon emissions, it may exacerbate lifecycle emissions. It highlights the importance of comprehensive emission assessment in …
Mbugua James Kamau, Waswa Gabriel Andati
This systematic review (78 articles, 2019-2026) evaluates biochar as an enhancement for urban Nature-Based Solutions (NbS) in African cities. Biochar improves soil infiltration by 40-60%, pollutant removal up to 80%, and sequesters 2.5-3 to…
Chih-Chun Kung, Clovis Awah, Philippe M. Heynderickx
This paper explores the potential of hydrothermal technologies for waste-to-energy, evaluating bioenergy production, economic viability, and carbon offset benefits. It examines the integration of waste treatment and energy recovery for deca…
Peng Zhang
This study prioritizes public investments for low-carbon rural e-commerce in China using an AHP-TOPSIS framework. Based on expert surveys and sensitivity analysis, skills and entrepreneurship support and low-carbon logistics investment emer…
Pallavi H J, Shiva Kumar G, R. Shanthi Vengadeshwari +4
This study experimentally evaluated concrete with bamboo and coconut shell biochar as cement replacements at 2%, 4%, and 6%, finding 4% optimal for strength, durability, and workability. Machine learning models predicted compressive strengt…
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