中国豫北県域における土地利用炭素排出の時空間動態と影響メカニズム
Spatiotemporal Dynamics and Influencing Mechanisms of Land-Use Carbon Emissions in Counties of Northern Henan, China (原題)
Zhigang Li, Yingying Zhao, Yawen Hou, Hongyu Lu, Haidong Li, Yunxing Zhang
🤖 gxceed AI 要約
日本語
中国豫北37県を対象に2000〜2020年の土地利用炭素排出（LUCE）を改良IPCC法で推計し、空間統計手法で時空間パターンと駆動要因を分析した。農地から建設用地への転換が進行し建設用地は45.6%増加、モラン指数は0.082から0.382へ上昇し空間集積が強まった。2010年以前は社会経済要因が支配的だったが、その後はNDVIなど自然要因と人為活動の交互作用が強まった。県レベルでの差異化された低炭素政策と土地利用最適化の枠組みを提示する。
English
Using an improved IPCC method, the study quantifies land-use carbon emissions (LUCE) across 37 counties in Northern Henan, China (2000-2020), analyzing spatiotemporal patterns and drivers via standard deviational ellipse, Moran's I, and a geographical detector. Construction land rose 45.6% as cultivated land converted, and spatial clustering strengthened (Moran's I 0.082 to 0.382). Socioeconomic drivers dominated before 2010, after which natural constraints (notably NDVI) and human-nature interactions gained prominence. It offers a fine-scale framework for differentiated county-level mitigation pathways.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国の県レベルという細粒度での炭素排出推計は、日本の自治体・地域脱炭素（ゼロカーボンシティ）やScope 3の地域別排出把握を検討する読者にとって方法論的参考になる。ただしSSBJや有報開示との直接的な接続は薄い。
In the global GX context
Adds sub-national, county-scale empirical evidence to the global stocktake of land-use emissions, relevant to territorial carbon accounting and spatial planning under national decarbonization pathways. It complements but does not directly engage TCFD/ISSB disclosure frameworks.
👥 読者別の含意
🔬研究者:土地利用由来排出の細粒度推計と地理的検出器を用いた駆動要因分析の方法論的枠組みを参考にできる。
🏢実務担当者:地域別・土地利用別の排出把握や拠点立地に伴う土地転換リスクの評価に応用可能。
🏛政策担当者:県・自治体レベルの差別化された低炭素土地利用計画と地域協働政策の設計に示唆を与える。
📄 Abstract（原文）
Climate warming driven by greenhouse gas emissions, especially carbon dioxide, severely threatens ecosystems and human societies. Accelerated by urbanization, land-use changes have significantly exacerbated climate change and disrupted carbon dynamics. Counties are key administrative units in China and are crucial for economic growth and achieving carbon neutrality goals. However, systematic research on carbon emission evolution and drivers at this scale remains scarce, hindering targeted low-carbon pathways. This study employs an improved IPCC method to quantify land-use carbon emissions (LUCE) in 37 Northern Henan counties (2000-2020). Using the standard deviational ellipse, Moran’s I, and an optimal parameter-based geographical detector, we analyzed spatiotemporal patterns and drivers. The results showed that (1) land transformation primarily involved converting cultivated land to construction land, with the latter increasing by 45.6%. The LUCE distribution exhibited stability, while global Moran’s I increased from 0.082 to 0.382, reflecting enhanced “high-high” and “low-low” spatial clustering. (2) Socioeconomic factors were the dominant drivers before 2010, while natural factors gained prominence thereafter. By 2020, natural constraints (especially NDVI) and their interactions with human activities (e.g., NTL) became key determinants, signaling intensified human‑nature coupling. (3) Given heterogeneous resources, we propose tailored pathways, including land use optimization, industrial transformation, and regional collaboration. This research establishes a fine-scale methodological framework for identifying complex driving mechanisms, offering scientific evidence for precise spatial planning and differentiated carbon mitigation policies at the county level to promote synergy between regional development and ecological sustainability.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.15244/pjoes/231512first seen 2026-10-17 04:49:42
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