gxceed
GX Research Hub · English

GX & Decarbonization Research

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.

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Topic: #Climate Science (clear)

Showing 441–446 of 446 papers

📚 Peer-reviewed · JournalAgroforestry Systems2026#Climate ScienceDOI

Impact of traditional agroforestry systems on biomass and carbon stock for climate change mitigation in the North-Western Indian Himalayas

Kapoor, Bhupender Gupta, Kiran Soni +3

This study assesses the impact of traditional agroforestry systems on biomass and carbon stock in the North-Western Indian Himalayas, highlighting their potential for climate change mitigation. Findings indicate that these systems enhance l…

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🇯🇵 Japan📚 Peer-reviewed · JournalJ-STAGE#Climate ScienceDOI

P23-4 Effect of Tillage Methods on Greenhouse Gas Emissions from Paddy-Upland Rotation Fields: A Case Study of Hokkaido Peat Soil Field Using LCA Method (Poster Presentation, 23. Global Environment, 2009 Kyoto Conference)

P23-4 耕起法が水田転換畑における温室効果ガス発生量に及ぼす影響 : LCA手法を用いた北海道泥炭土圃場の事例(ポスター紹介,23.地球環境,2009年度京都大会)

(著者不明)

This study evaluates the impact of different tillage methods on greenhouse gas emissions from paddy-upland rotation fields in Hokkaido peat soil using LCA methodology. It provides insights for GHG mitigation in agricultural practices.

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🇨🇳 China📚 Peer-reviewed · JournalSustainable Development2026#Climate ScienceDOI

Agricultural Land Use Change and Environmental Quality Nexus: Implications for Sustainable Development Goals 11, 13, and 15

Shah Fahad, Aftab Khan, Muhammad Luqman +1

This study examines the impact of arable land, grazing land, and forest area changes on CO2 emissions in Pakistan from 1990-2021 using ARDL. Forest area reduces emissions by 25.98% short-run and 17.10% long-run; grazing land increases emiss…

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🌍 Global📚 Peer-reviewed · JournalFrontiers in Climate2026#Climate ScienceDOI

Deep learning model anticipates climate change induced reduction in major commodity crop yields for Canada in 2050

Amanjot Bhullar, Khurram Nadeem, Nathaniel K. Newlands +2

This study uses deep learning to predict the impact of climate change on major crop yields in Canada. It projects declining suitability for canola, peas, spring wheat, and soy in the Prairies by 2050, with gains for barley and oats. Net los…

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