GX Research Hub · English

GX & Decarbonization Research

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.

📊 SNE Research Profile →🔬 Researcher API →About gxceed →🇯🇵 日本語版
Shelf:All Papers🇯🇵→🌍 Japan-to-Global🌍→🇯🇵 Global-to-JapanCurated
Sort:NewestRelevanceMost Viewed
Topic: #Climate Risk (clear)

Showing 81–100 of 364 papers

🇺🇸 USAJournalZenodo (CERN European Organization for Nuclear Research)2026#Climate RiskDOI

Reproducibility Code and Processed Data for "Equity-Aware Multi-Objective Optimization of Nature-Based Solutions for Flood Susceptibility Reduction"

Chibuike Chiedozie Ibebuchi

This package provides code and processed data for reproducing a study on equity-aware multi-objective optimization of nature-based solutions (tree planting, wetland restoration) for flood susceptibility reduction. It includes 4,079 Maryland…

Read more →
Peer-reviewed🌍 GlobalJournalnpj Urban Sustainability2026#Climate RiskDOI

Integrating risk and feasibility in the spatial planning of nature-based solutions: a cross-city analysis of Barcelona, Boston, and Rotterdam

Svetlana Khromova, Svea Busse, Giulia Benati +5

This paper develops a transferable, SETS-based decision-support framework for spatially analyzing multi-hazard climate risk and feasibility of four nature-based solutions (green roofs, permeable pavements, rain gardens, urban parks) across …

Read more →
Peer-reviewedJournalZenodo (CERN European Organization for Nuclear Research)2026#Climate RiskDOI

STRATEGIC POLITICAL ECONOMY OF TAMIL NADU'S EMERGING GROWTH MODEL: AN INTEGRATED ANALYSIS OF ECONOMIC RESILIENCE, FINANCIAL STABILITY, GEOPOLITICAL STRATEGY, ENERGY SECURITY, DIGITAL TRANSFORMATION, INFRASTRUCTURE DEVELOPMENT, CLIMATE RISKS, AND INNOVATION-DRIVEN SUSTAINABLE DEVELOPMENT IN A CHANGING GLOBAL ORDER

Dr. G. YOGANANDHAM

This research analyzes Tamil Nadu's growth strategy as an integration of industrial development, technological progress, and sustainability. It focuses on energy security, digital transformation, and climate resilience, assessing responses …

Read more →
Peer-reviewed🇯🇵→🌍 Japan-to-Global🇯🇵 JapanJournalFrontiers in Sports and Active Living2026#Climate RiskDOI

The climate change dilemma of ski destinations: adaptation becomes maladaptation

Ching Li, Ting-Yen (Tim) Huang, Jia-Rui Zheng

This study analyzes maladaptation risks in Japan's ski industry, where adaptation measures can create new vulnerabilities. Using an elevation-based Snow Reliability Line (SRL) screening framework with JMA climate data and resort documents, …

Read more →
Peer-reviewedJournalJurnal Pengawasan Tenaga Nuklir2026#Climate RiskDOI

Addressing the Resilience Issues of NPP to Climate Change Through the CNS and VDNS: An Evaluation of Applicability from the Perspective of Indonesia as an Embarking Country

Reno Alamsyah, Anggoro Septilarso

This paper examines how climate change affects nuclear power plant (NPP) safety and how international frameworks (CNS and VDNS) can enhance resilience. It proposes ways for embarking countries like Indonesia to strengthen national regulatio…

Read more →
Peer-reviewedCNJournalSN Business & Economics2026#Climate RiskDOI

A PINN-inspired structure-regularized framework for climate and geopolitical risk in agricultural commodity markets: evidence from China

Yesser Drira, Souha Boutouria, Mouna Boujelbène

This paper proposes a structure-regularized framework inspired by physics-informed neural networks (PINN) to analyze the impact of climate and geopolitical risks on agricultural commodity markets in China. It applies AI methods to improve r…

Read more →
Peer-reviewedJournalScientific Reports2026#Climate RiskDOI

Harnessing geospatial and machine learning technologies to simulate ecosystem services and greenhouse gas emissions in a dynamic watershed system of Haramaya Lake, Ethiopia

Gemechis B. Mosisa, James Akuku, Abel Mwembe +5

This study simulates ecosystem services and greenhouse gas emissions in the Haramaya Lake watershed, Ethiopia, using geospatial and machine learning techniques. It assesses the impacts of land-use change on ecosystems and climate, offering …

Read more →
← Prev5 / 19Next →

Browse by Topic

#Scope 3#Scope 1/2#Carbon Pricing#Renewable Energy#Policy#TCFD#SBT/SBTi#CDP#CCUS#Hydrogen#Climate Finance#Climate Science#EV & Transport#Energy Transition#ESG#Transition Finance#Greenwashing#Climate Risk#Biodiversity#Carbon Accounting#Disclosure Infrastructure#Energy Efficiency#Supply Chain#AI × ESG#Other