炭素収支ゾーニングを考慮した水炭素ネクサス下の多目的水配分—経済発展地域における検討
Carbon balance zoning-informed multi-objective water allocation under the water-carbon nexus in economically developed regions (原題)
Zhuoyue Peng, Xinran Zhang, Mengting Li, Yaming Liu, Hongyuan Fang, YIN Junxian
🤖 gxceed AI 要約
日本語
経済発展地域の水需給と炭素収支の課題に対し、「炭素収支分析→水需要予測→水炭素ネクサス→多目的最適化→方案評価」の枠組みを構築した研究。InVESTモデルで炭素吸収源を推定し、蘇州・無錫・常州・鎮江・南京など炭素不均衡が深刻な地域を特定。NSGA-IIによる多目的最適化とエントロピー重み-TOPSISで方案を選別した結果、低炭素シナリオでは2030年の水不足率が13.90%から6.07%へ改善し、炭素排出も最大13.02Mt削減されることを示した。
English
This study builds a framework linking carbon balance analysis, water demand forecasting, and multi-objective optimization to allocate water under the water-carbon nexus in developed Chinese regions. Using InVEST and NSGA-II with entropy-weight TOPSIS, it identifies five carbon-imbalanced cities and shows a low-carbon scenario cuts water shortage rates from 13.90% to 6.07% and emissions by up to 13.02 Mt by 2030. Carbon-deficit regions drive most reductions, demonstrating spatially targeted water-carbon synergy.
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「双炭」目標下での地域水資源・炭素統合管理の定量手法であり、日本のSSBJ・有報開示や企業の水リスク(Scope 3・水会計)対応に直接接続するものではないが、流域単位の炭素収支と水配分を結びつける発想は自治体・事業者の水炭素統合計画の参考になる。
In the global GX context
The paper offers a quantitative water-carbon nexus optimization method aligned with China's dual-carbon goals, contributing a regional (basin-level) perspective that complements corporate-level TCFD/ISSB water and carbon disclosure. It is relevant to global scholarship on subnational climate-water planning rather than to disclosure frameworks directly.
👥 読者別の含意
🔬研究者:水と炭素を統合した多目的最適化と炭素ゾーニング評価の手法設計の参考になる。
🏢実務担当者:流域・地域単位の水リスクと炭素削減を同時に検討する際のシナリオ・評価手法として参照可能。
🏛政策担当者:地域の水配分計画に炭素収支ゾーニングを組み込む政策設計の定量根拠を提供する。
📄 Abstract（原文）
Focusing on water supply-demand and carbon balance challenges in economically developed regions, this study develops a systematic framework of “carbon balance analysis→ water demand prediction→ water-carbon nexus→ multi-objective optimization→ scheme evaluation”. The InVEST model estimates carbon sink capacity and identifies regions with severe carbon imbalance (Suzhou, Wuxi, Changzhou, Zhenjiang, Nanjing) based on carbon supply-demand ratios. Current development and low-carbon scenarios are set considering population, urbanization, and industrial structure. A multi-objective optimization model is constructed to minimize water deficit and carbon emissions, solved by NSGA-II. An entropy weight-TOPSIS method integrated with carbon zoning results is applied for scheme screening. Results show: (1) Carbon sinks exhibited a “high north, low south” pattern with declining totals from 2005 to 2020, while emissions concentrated in the south and nearly doubled. (2) Under 2030 P = 75% inflow frequency, water shortages occur under both scenarios; however, the low-carbon scenario significantly improves the shortage rate from 13.90% to 6.07%. (3) Carbon emissions are reduced by 13.02 Mt. and 11.17 Mt. under 50% and 75% frequencies, with the five imbalanced regions contributing 56.85% and 62.37% of total reductions under low-carbon scenario. The five carbon-deficit regions serve as the primary contributors to these reductions, highlighting the spatial effectiveness of low-carbon water allocation. This study reveals water-carbon synergistic regulation patterns and provides quantitative decision support for sustainable water management under the “dual carbon” goals.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.ecolind.2026.115725first seen 2026-10-23 05:22:36 · last seen 2026-11-06 04:57:11
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