炭素源・吸収源の時空間動態と純炭素排出量の駆動メカニズム：長江経済ベルトを事例に
Spatiotemporal dynamics of carbon sources and sinks and driving mechanisms of net carbon emissions: a case study of the Yangtze River Economic Belt (原題)
Duo Tan, Maojuan Li, 童小梁, Liyun Zhang, Tianqi Li
🤖 gxceed AI 要約
日本語
長江経済ベルトを対象に、純生態系生産性（NEP）から炭素吸収量を推計し純炭素排出量（NCE）を算出。2000年の1188.56Mtから2022年には3656.60Mtへ増加し、上流から下流へ増加する勾配と正の空間自己相関を確認した。PLS-PM分析により、社会要因がNCEに正の直接効果、生態要因が負の直接効果、経済要因が間接効果を持つことを示し、人間・環境システムの共進化がNCEの時空間分化の核心メカニズムだと結論づけた。
English
Using net ecosystem productivity to quantify carbon sinks, this study estimates net carbon emissions (NCE) for China's Yangtze River Economic Belt, rising from 1188.56 Mt in 2000 to 3656.60 Mt in 2022 with significant positive spatial autocorrelation. PLS-PM analysis shows social factors have strong positive direct effects on NCE, ecological factors negative direct effects, and economic factors indirect effects, identifying human-environment system co-evolution as the core driver of NCE differentiation.
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
中国の地域炭素収支研究であり、日本のSSBJ・有報開示や企業のScope算定に直接資するものではないが、地域単位の吸収源評価手法は自治体・地域脱炭素計画の参考になり得る。
In the global GX context
Adds regional-scale evidence on net carbon accounting that complements corporate-level disclosure frameworks (GHG Protocol, ISSB) by quantifying territorial sources and sinks; relevant to subnational decarbonization planning rather than firm-level reporting.
👥 読者別の含意
🔬研究者:地域スケールの純炭素排出推計とPLS-PMによる駆動要因分解の手法例として参照価値がある。
🏛政策担当者:地域別の低炭素戦略設計において、社会・経済・生態要因の協調的調整が有効である点を政策立案に活用できる。
📄 Abstract（原文）
The scientific quantification of regional net carbon emissions (NCE) and the elucidation of their underlying mechanisms are of great significance for advancing sustainable development. However, carbon-related research has long suffered from a separation between sources and sinks, and there remains a lack of systematic understanding of the driving mechanisms behind NCE. Taking the Yangtze River Economic Belt (YREB) as a case study, this research quantifies carbon sinks based on net ecosystem productivity (NEP) to estimate NCE, and employs correlation analysis and partial least squares path modeling (PLS-PM) to elucidate the influencing mechanisms of NCE and its relationship with the human-environmental system (HES). The results indicate that carbon sources and NCE exhibited a clear upstream-to-downstream increasing gradient, opposite to the pattern for carbon sinks, with total NCE rising from 1188.56 Mt (2000) to 3656.60 Mt (2022) Meanwhile, carbon sources, sinks, and NCE all exhibit significant positive spatial autocorrelation (p < 0.01). Among the influencing factors, urbanization rate (UR), energy consumption per unit of GDP (UEPV), and normalized difference vegetation index (NDVI) demonstrate significant correlations (p < 0.01), though key influencing factors vary regionally, with global correlation coefficients generally increasing. From an HES perspective, social factors exert a strong positive direct effect on NCE (mean path coefficient = 0.497, p < 0.01), while ecological factors have a direct negative effect (mean path coefficient = −0.267, p < 0.05, except in 2006). In contrast, economic factors primarily produce an indirect effect (mean path coefficient = 0.163, p < 0.01). This study demonstrates that the synergistic evolution of the HES is the core mechanism underlying the spatiotemporal differentiation of NCE. It is recommended that region-specific low-carbon strategies be implemented through the coordinated regulation of social, economic, and ecological systems to achieve the dual carbon goals in the YREB.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3389/fenvs.2026.1917084first seen 2026-11-01 05:01:53 · last seen 2026-11-06 04:57:58
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