This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open 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 19901–19920 of 20907 papers
Hanwei Zhang, Haibin Liu, Xuena Liu
This paper empirically examines the impact of environmental information disclosure on debt financing for Chinese listed steel companies (2014-2023). Findings show that environmental disclosure reduces debt financing costs and improves finan…
Dzakiyy Hadiyan Achyar
This study investigates Islamic green financing (IGF) for renewable energy in GCC countries from 2019-2023 using a fixed effects model. It finds that IGF enhances solar-based renewable technologies through energy efficiency and climate poli…
null Muhammad Adnan Afzal, null Saif Ur Rahman, null Muhammad Toseef Aslam
This bibliometric analysis of 498 green technology articles (2004-2025Q1) reveals a shift from technology-centric to systemic-transition science. China leads in output and citations but is embedded in dense international collaborations. Eco…
Yong Hu, Altaf Hussain Pirzado, Yongting Wang
This paper examines China's carbon account system using Ant Forest as a case study, proposing a collaborative model integrating EV manufacturers with internet-based green finance platforms. Based on survey data, it addresses standardization…
Wang Ying, Muhammad Ramzan, Victoria Olushola Olanrewaju +2
This study examines the impact of women in politics, democracy, and patent innovations on renewable energy adoption in the UK from 1997 to 2021 using wavelet-based quantile techniques. Results show that women in politics and patents consist…
Ozge Demirkale, Naime Irem Duran
This study examines predictive relationships between the WilderHill Clean Energy Index and tourism stock indices from the US, Europe, China, and Australia using quantile Granger causality and wavelet coherence on monthly data from 2010-2023…
Hakan İnal, Emma Karlsson, Oliver Nåfors +2
This study compares the life cycle cost (LCC) of BEV, PHEV, and ICEV in Sweden in 2024. The Tesla Model Y (BEV) has an LCC of 877,736 SEK, the Volkswagen T-Roc (ICEV) the lowest at 635,222 SEK, and the Volvo XC60 (PHEV) the highest at 1,104…
Carlo Drago, Massimo Arnone, Angelo Leogrande
This paper analyzes N2O emissions from an ESG perspective using econometric and machine learning methods. It identifies forest degradation, energy intensity, and income inequality as key determinants. Developed nations, despite better effic…
Zhang, Junkang, Fan, Hongmin, Chen, Mo +2
Using a dataset of 4,181 Chinese listed firms (2012-2022), this study finds that climate risk shocks significantly increase corporate labor outsourcing expenditures. The effect is stronger for firms with limited cost-passing capacity and hi…
bioenergy science
This article comprehensively reviews Life Cycle Assessment (LCA) for bioenergy systems, covering methodologies, challenges, and future directions. It discusses attributional vs. consequential LCA, handling of biogenic carbon and indirect la…
Patel, Khushali
This paper comprehensively reviews how climate risks translate into financial vulnerabilities in emerging markets. It analyzes physical, transition, and liability risk mechanisms, and evaluates adaptation measures such as climate disclosure…
Mahmudi, Sedat, Dik, Roula
This paper empirically analyzes how conventional economic and financial metrics influence solar energy investment in Kuwait using 13 years of data. A multiple linear regression finds that only LCOE is marginally significant, while other met…
F. A. Samiul Islam
This study proposes an AI-driven Smart Waste-to-Energy framework (AI-CIR-WtE) integrating LSTM, NSGA-II, digital twins, and blockchain for Dhaka, Bangladesh. It forecasts waste generation, optimizes routing and energy efficiency, and quanti…
israeli, johnny
This paper reviews challenges and strategies for building sustainable urban energy systems in developing economies. It identifies barriers such as insufficient infrastructure, limited funding, fossil fuel dependence, policy gaps, and rapid …
Benedict Afful, Kassim Alabani
This study uses dynamic panel analysis to examine how national innovation capacity affects the decoupling of economic growth from carbon emissions. It finds that higher innovation capacity contributes to emission reductions, highlighting th…
Horn, Sarun, Tang, Kimsreang, Ngan, Panha
This narrative review synthesizes IPCC Tier 1-3 methods for forest carbon accounting, National Forest Monitoring Systems (NFMS), and integration of remote sensing with field inventories, including machine learning. It highlights trade-offs …
Kunal Patil
This paper proposes a framework for demand-side sufficiency—prioritizing absolute reductions in resource and energy consumption through structural and behavioral shifts—as a necessary complement to efficiency gains for meeting the 1.5°C tar…
Sate Sampattagul, Phakphum Paluang, Shabbir H. Gheewala +1
This study develops a replicable, data-driven framework for subnational climate action, demonstrated through a case study of Chiang Mai, Thailand. It integrates a comprehensive GHG inventory with spatial analysis to identify location-specif…
Clilverd, Hannah, Williamson, Jennifer, Nickerson, Rachel +2
Saltmarshes are vital for blue carbon storage but have historically emitted CO2 due to drainage and land-use change. This study uses Google Earth Engine to develop a satellite-based model for annual monitoring of saltmarsh vegetation cover …
Myeong-Gyun Kim, Se-Young Kim, Hyo-Jong Song
This study develops a high-resolution road-level CO₂ emissions inventory for South Korea using machine learning (RF, LGBM, XGBoost, DNN) to estimate traffic volumes where observed data are lacking. Models achieved high accuracy (R² up to 0.…
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