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 19801–19820 of 36021 papers
Jennifer Michel
Rhizosphere priming effects (RPE) are often assumed to accelerate soil organic matter turnover and net carbon loss. This paper challenges that paradigm by showing that positive and negative RPE can cancel, leading to neutral or positive net…
Weizhi Wang, Rongfu Sun, Zhenjiang Shi +4
This paper addresses the 'separation of certificate and power' problem in cross-province green power trading under China's East Data, West Computing project. It proposes using Physical Transmission Rights (PTRs) as compliance certificates f…
N. Mhetras, D. Gokhale
This review summarizes recent developments in biofuel production from lignocellulosic biomass (LCB), highlighting its potential as a sustainable renewable resource. High costs of pretreatment and enzymatic hydrolysis remain key barriers. In…
Gaoneng Lai, Lei Jiang, Yingbiao Chen +3
Using remote sensing and spatial econometric models, this study analyzes the relationship between urban heat island effect and CO2 emissions in the Yangtze River Delta, finding that the mediation effect of energy activity intensity accounts…
Sorana Vătavu, O. Lobonţ, Dumitrița Gîrlă +3
This study uses panel data from EU member states (2000-2021) to examine the relationship between corporate environmental governance and GHG emissions in energy-intensive industries. It estimates elasticities of emissions to sectoral value a…
M. C. Ausín, A. Sarhadi, M. Wiper
This paper presents a Bayesian spatio-temporal modeling framework for hurricane risk assessment along the U.S. coasts. Using high-resolution synthetic cyclone data and INLA, it captures the spatiotemporal variability of wind hazards and joi…
Janardhana Anjanappa, Vishal Singh
This qualitative synthesis examines climate risk perception, disclosure, and financing in India's urban real estate. It identifies a cycle of vulnerability due to limited investor awareness, absent disclosure tools, and non-differentiated l…
Duan Liu, Ziyu Sang, Hong Wan +1
Using a sample of Chinese listed firms' corporate bonds from 2015-2021, this study finds that climate information disclosure heightens investors' risk perceptions, amplifying the impact of climate risk on bond credit spreads and increasing …
Irfan Budiyanto
This study assesses the feasibility of coal-to-nuclear (C2N) conversion in Indonesia, targeting net zero by 2060. It evaluates PLN Nusantara Power's coal-fired units using technical criteria (capacity >200 MWe, age ≤15 years), natural disas…
Hao Li, Steffen Knoblauch
This position paper examines responsible GeoAI for climate extreme and disaster mapping from a critical GIS perspective. It proposes four theoretical dimensions (Representativeness, Explainability, Sustainability, Ethics) and a governance m…
Ramota Obagah-Stephen, Inemi Erete Stephen
This paper investigates the loss of documentation for six historic legislative buildings in Nigeria, identifying four mechanisms of organizational forgetting. It argues that documentation governance is prerequisite for climate-adaptive cons…
Daniel Harris, Suleman Ayub Khan, Swathi Balasubramanian +3
This review evaluates Life Cycle Assessment (LCA) methodologies for 3D concrete printed (3DCP) buildings and their alignment with the revised Energy Performance of Buildings Directive (EPBD), which requires whole-life Global Warming Potenti…
M. Uddin, Md. Samsuzzaman Sobuz, Mohamed Ghalla +5
This study developed a hybrid machine learning model (XGB-HistGB) to predict compressive strength, cost, and CO2 emissions of biochar-incorporated concrete. Using a dataset of nine input parameters, the model achieved high accuracy (R2=0.95…
Gunturu Sai Pragna, L. Prasanna, Nayab Mahaboob Subhani
This paper investigates the use of supplementary cementitious materials (SCMs) such as silica fume, metakaolin, and fly ash as partial replacements for cement in concrete to reduce environmental impact and improve performance. The optimized…
Umunna, Chetachi C., Okoroafor, Humphery K.
This paper critically examines architecture's dual role in climate change—as a major emitter and a mitigation tool. It reviews global case studies, advocates for a shift from extractive to regenerative practices, and proposes a framework in…
A. Windapo, Darmarajan Chinasamy, K. Alade
This paper reviews 18 peer-reviewed publications on regenerative construction (2020-2025), identifies benefits (whole-life asset value, cost reduction, circular economy, ecological restoration, embodied carbon reduction) and limitations (hi…
Chaitali Trivedi, M. Pathak, S. Dhar
This study evaluates decarbonization strategies for embodied carbon from cement and steel in residential buildings in Ahmedabad, India, using the IPCC AR6 framework and AIM/End-use model. Results show that energy efficiency and clean techno…
Ololade Temitope Oduneye
This paper examines geopolymer concrete (GPC) as a sustainable, low-carbon alternative to Portland cement. It discusses GPC's materials (fly ash, slag), durability, applications, and challenges such as cost and availability, along with futu…
Jiaran Liu, Yuheng Huang
This study proposes GBMP-LCA, a gradient boosting–based framework for performance prediction and life-cycle optimization of green building materials. It applies LightGBM to multi-source features including material composition, durability, a…
Dilba Rayaru Kandiyil, M. Sadique, Denise Lee +2
This study proposes a hybrid ML-LCA framework to estimate cement embodied carbon using only publicly available macroeconomic data, predicting clinker-to-cement ratio from GDP per capita and other indicators. The Gradient Boosting model is i…
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