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 541–560 of 31386 papers
Rogelio Omar Corona-Núñez
Using 992 household surveys and Random Forest spatial modeling, this study maps per-capita household carbon footprints (diet, housing, transport) across the Mexico City Metropolitan Area at 100-m resolution. It shows urban structural and in…
Abbas H. Abdulabbas, Afnan H. Ali, Murtada Ameer Ismael +1
This study analyzes replacing cement, sand, and gravel in concrete with industrial and plant wastes to cut CO2 emissions, embedded energy, and cost. Drawing on 30 published studies (2007–2023), it finds reductions of 2–100% depending on the…
Lawrence Oladeji
SiteFootprint estimates operational carbon emissions and on-site water use of AI training at any location, computing hourly data-centre cooling from real weather and combining it with grid carbon intensity, with 95% uncertainty ranges and p…
L. Campion, M.J. Spaniol, T.P. Thomsen
This study maps future pathways for biochar carbon removal (BCR) in Denmark using expert interviews, stakeholder ranking, and scenario modeling. Four critical uncertainties emerge—subsidies, carbon prices, agricultural-use regulation, and b…
Andekujwo Baajon MAMMAN
Using 1970–2024 Nigerian data, this study applies ARDL bounds testing and Toda-Yamamoto causality to examine CO2 emissions, energy consumption, and economic growth. Long-run effects of emissions and energy use on growth are negative, while …
J Sophia Rosaline, D.Praveena
This study examines how carbon footprint disclosure shapes consumer behaviour through trust, environmental concern, brand credibility, and purchase intention. Using questionnaire data and SPSS analysis, it finds transparent carbon labelling…
Andriy Helesh, N. R. Lysyy, Pavlo B. Saik +3
This study thermodynamically compares four idealized carbon gasification routes for carbon-containing waste (coal mining waste as example) at 660-1000°C. Using unified indicators (heat requirement, resource heat, thermal self-sufficiency co…
Yang Xu, Tianci Gu, Feng Xu +6
A dual-constraint spatial planning framework couples habitat suitability with land-sea anthropogenic pressures across China's 18,000-km coastline. Integrating 60 environmental variables and 13 pressure indicators reveals blue carbon expansi…
David Carter, Jason P. Coumans, Nail R. Zagrtdenov +2
This study tests bio-carbon (BC) as a substitute for petroleum coke (PC) in CaCl2-assisted direct reduction of chromite. BC accelerated reduction kinetics via devolatilization-driven microporosity, advanced peak CO flux by 8 minutes, and yi…
Yang Yu, Xinyi Yang, Jiaqi Liu +1
Using 2007–2021 panel data for 16 Chinese industrial sectors, this study examines how carbon regulation and global value chains (GVCs) shape technological innovation, with projections to 2040. Carbon regulation generally promotes innovation…
Milan Perazich
Supplementary material for an article examining public accountability for carbon storage credits in the US and Canada. Part S1 documents the verification record (source tiers, search universe, dated checks); Part S2 describes two deposited …
Angela Cuttitta, Marilena Di Natale, Marianna Musco
This policy brief argues that EU carbon removal frameworks (LULUCF, ETS, Regulation 2024/3012) focus almost exclusively on terrestrial ecosystems, excluding marine Blue Carbon sinks such as Posidonia oceanica meadows. While immediate LULUCF…
Abdurahman Abba Goni, Mustapha Shettima, Mohammed Buba
A PRISMA 2020 systematic review synthesizing 102 eligible studies (from 4,827 screened, 2010–2024) on spatially targeted nature-based solutions for urban climate hazards—heat, flooding, drought, air pollution. Finds NbS (SUDS, green spaces,…
Jiexuan Zhou, Ying Chen
This paper proposes a low-carbon optimization framework for a multi-energy distribution network coordinating electricity, gas, heat, and hydrogen with Power-to-X, hydrogen blending, carbon capture, and aerial electric mobility. It integrate…
Roland Condor, Brigitte Daudet
This paper examines how 'proximities' act as agents in local carbon offsetting within agriculture. It explores how geographic and social proximity shape the actors and implementation of offset schemes. Though no abstract is available, it of…
Mohammad Alrbai, Sameer Al‐Dahidi, B. Kalidasan +6
This review systematically assesses renewable-energy-driven CCUS systems across technical, economic, environmental, policy, and deployment dimensions. It quantitatively compares leading CO2 capture methods on efficiency, energy penalty, TRL…
Hung Vo Thanh
This study analyzes the viability of coupling carbon capture and storage (CCUS) with underground hydrogen storage (UHS) in shared subsurface space, using geocoded data on 135 CCUS projects and 42 UHS facilities plus a techno-economic model.…
Yuewen Huang, Tong Zhang, Meng Chen +1
A multi-scale study on using carbonated recycled concrete fines to improve the thermal resistance of low-carbon cementitious materials. It offers material-design insights that combine construction decarbonization with waste valorization.
Yi Xing, Ruijie Wang, Guilan Yi +1
Stainless-steel slag was carbonated at efficiencies of 1.21–11.68% and blended into mortar to study strength mechanisms. The 28-day compressive strength showed a U-shaped response with a minimum at 3.33% and a compensation point at 3.95%, d…
Zhijie Li, Zhongli Wang, Madoka Taniguchi
A systematic review of 172 peer-reviewed studies applying machine learning to compressive strength prediction of low-carbon concrete (LCC). Bibliometric and methodological analysis reveals a shift from single models to ensemble learning, Ba…
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