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 41–60 of 439 papers
Guanna Pan, Ulrike Kornek, Chen Chris Gong +3
This study quantifies climate-related assets for 169 countries across fossil fuel production, climate damages, renewable potential and land carbon sequestration, combining IAMs, climate projections, damage functions and biosphere data under…
Horacio A. Aguirre, Kamila Aguirree, João Ayres +3
This paper examines how environmental physical and transition risks affect central banks in Latin America and the Caribbean, impacting inflation, credit supply, and financial stability. It reviews how central banks have integrated these ris…
Mohammad Haseeb, M. A. Esquivias, Md Emran Hossain +3
Examines how attention to climate-risk narratives in corporate disclosure relates to actual carbon emissions. Internal governance and coal efficiency act as moderators, while green innovation serves as a mitigating channel linking narrative…
Aharon D.Y.
A study examining the relationship between greenhouse gas emissions and the stability of equity markets. Without an abstract, details are unclear, but it likely empirically tests how emissions and climate-risk factors affect stock volatilit…
Yong-Jing Gao, Ya-Han Dong, Norman Mohd-Saleh +2
Using Chinese A-share firms (2010-2023) and the Climate Adaptation City Pilot Program, this study finds higher corporate climate risk disclosure intensity in pilot locations, though DID assumptions are only partially satisfied. The detectab…
Xinzhu Wang, Jiatong Dong, Mengmeng Pan
Using panel data from Chinese A-share listed firms (2010-2023), this study finds climate risk promotes open green innovation via rising external green demand and internal resource constraints. Heterogeneity shows firms with stronger green n…
Yuqin Zhou, Zixuan Luo, Shan Wu
This paper analyzes spillovers between climate physical/transition risks and carbon, energy, and metals markets using higher-moment risk measures (return, volatility, skewness, kurtosis) within a quantile time-frequency framework. Higher-mo…
Shahana Bilalova, Marthe Wens, Laurine de Wolf +1
A study on co-creating implementation strategies for nature-based solutions (NbS) to manage flood and drought risk, using the GEUL basin in the Netherlands as a case. It highlights participatory, stakeholder-driven planning for climate adap…
Gambhir A.
This paper jointly assesses the near-term transition risks (policy, technology, market shifts) and longer-term physical climate risks associated with different GHG emissions pathways. It shows how the pace and shape of decarbonization creat…
A. M. Mostafa, A. Khwaldeh, A. Imran +2
Proposes a hybrid DenseNet121–MobileNet deep learning model for climate change prediction and sustainable climate risk management. It adapts image-recognition CNNs to extract patterns from climate data. No direct application to ESG disclosu…
Tong Niu, Si-Yu Zhu, Lu-Lu Qin
An interpretable ANN (MLP + SHAP) quantifies transmission pathways from physical and transition climate shocks to corporate default risk. For 1,232 listed firms across North America, Europe, and Asia-Pacific (2014–2023), one-quarter-ahead P…
A. Ptak-Chmielewska, P. Kopciuszewski
Using Southern European retail mortgage and unsecured loan portfolios (2008-2023), the study merges debtor-level, macroeconomic, and NGFS Phase IV transition scenario data to model PD under climate stress. PD predictions show a declining tr…
Krzysztof Lewandowski
This study introduces the Transport Infrastructure Impact Index (TIII), a reproducible engineering indicator combining three hydrometeorological variables (max precipitation, flooded area, duration) with four infrastructure variables (roads…
Elie Matta, Emile Whaibeh, Lea Kai +14
This study develops nationally tailored standards for climate-resilient, environmentally sustainable hospitals in Lebanon, translating WHO and ISO frameworks into context-specific guidance aligned with Lebanese law. The resulting 10 themati…
Priiyha M.P.
This study spatially maps agroclimate vulnerability and carbon emissions across India to inform its net-zero transition. It aims to identify priority regions where adaptation and mitigation efforts overlap. Without an abstract, methods and …
C. Watson, Lauren D. Rawlins, M. Chand +6
This study quantifies changes in building and population exposure to flooding in Nepal and transboundary India-China regions using high-resolution data. Validating five building footprint products, Google Open Buildings Temporal 2.5D achiev…
Thanh Nguyen Vinh
Using PVAR and dynamic panel threshold models for seven countries (2002–2022), this study examines the non-linear link between energy public–private partnerships (PPPIE) and climate risk. PPPIE shocks raise climate risk transitorily, peakin…
Liviana Sciuto, Viviana Pappalardo, Francesco Martinico +5
This study develops an integrated methodology combining HEC-RAS hydrological-hydraulic modelling, spatial analysis, and planning criteria to identify and prioritize Nature-Based Solution (NBS) sites in the densely built Tondo Gioeni catchme…
USHMEET KAUR, Wasim Ahmad
An empirical study examining the link between carbon emissions intensity and idiosyncratic stock volatility among Indian firms. It suggests how carbon-intensive firms are priced for firm-specific risk, contributing evidence on climate-relat…
Yi-Zhan Lian
Using Reuters news-based Transition Risk (TRI) and Physical Risk (PRI) indices, this study estimates VAR systems across six markets (carbon futures, gold, equities, insurance, agriculture, clean energy). Generalized forecast error variance …
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