LEAP-CMAQ連成モデルによる汚染・炭素協同削減：中国の石炭資源省における時空間進化とリスク評価
Coupled LEAP-CMAQ Modeling for Pollution–Carbon Coordination: Spatiotemporal Evolution and Risk Assessment in a Coal Resource Province of China (原題)
Miao Zhang, Xiaofei Ma, Chuang Liu, Xueying Jia, 尹晓敏
🤖 gxceed AI 要約
日本語
本研究は中国山西省を対象に、LEAP-CMAQ連成モデルと三次元ベクトルモデルを統合し、2026～2050年のエネルギー消費、CO2、主要大気汚染物質排出をシナリオ別にシミュレーションした。政策シナリオは長期的な低炭素性能が高く、排出削減と空間パターン最適化に有効だが、住宅・交通部門の排出削減やCO・NO2と炭素排出のデカップリングに課題が残る。系統的で長期的な低炭素ガバナンスが石炭資源地域のグリーン転換の核心であると結論づけ、段階的・分類的な協働ガバナンス戦略を提案した。
English
This study develops an integrated LEAP-CMAQ coupled framework with a three-dimensional vector model to simulate energy consumption, CO2, and air pollutant emissions in Shanxi Province, China, under Baseline and Policy scenarios (2026-2050). The Policy scenario achieves superior long-term low-carbon performance and optimizes spatial emission patterns, but faces challenges in residential and transport sectors and strong coupling of CO, NO2 with carbon emissions. The findings emphasize systematic, long-term low-carbon governance as the core driver of green transition in resource-based regions, proposing phased and classified collaborative governance strategies.
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
日本のGX文脈では、石炭依存地域の移行戦略や汚染・炭素の同時削減アプローチが、福島や北海道などの地域振興やカーボンニュートラル政策に示唆を与える。特に、SSBJ開示やトランジション戦略の策定において、地域特性を考慮した長期的な排出削減計画の重要性を再認識させる。
In the global GX context
This study contributes to global GX scholarship by demonstrating an integrated modeling approach for pollution-carbon synergy in coal-dependent regions, relevant for just transition planning and climate policy design. It provides empirical evidence on the effectiveness of policy scenarios in decoupling pollutants from carbon emissions, offering insights for regions undergoing energy transition. The methodological innovation of coupling LEAP and CMAQ can inform similar assessments in other resource-based economies.
👥 読者別の含意
🔬研究者:Provides a novel integrated modeling framework (LEAP-CMAQ) for assessing pollution-carbon synergy, useful for future research on regional energy transition and emission reduction.
🏢実務担当者:Offers insights for corporate sustainability teams in coal-dependent regions on the importance of long-term low-carbon strategies and sector-specific emission reduction measures.
🏛政策担当者:Highlights the need for systematic, long-term governance and phased, classified strategies for green transition in resource-based regions, informing policy design.
📄 Abstract（原文）
Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO2, and major air pollutant emissions (CO2, CO, SO2, NO2, PM2.5, and PM10) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO2 and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18178763first seen 2026-08-29 04:47:04
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