Low-Carbon Spatial Planning Strategies for Townships: A Carbon Accounting and Efficiency Evaluation Framework Applied to Fuqiushan Township
町レベルの低炭素空間計画戦略:福岐山町を事例とした炭素会計と効率性評価のフレームワーク (AI 翻訳)
Chun Yi, Yijun Chen, Bin Liu, Zixuan Wang, Xiangjie Zou
🤖 gxceed AI 要約
日本語
本研究は福岐山町を事例に、町スケールの炭素排出・吸収量を詳細に計測し、空間可視化と効率性指標を開発した。低炭素発展の総合指標を用いて5つのゾーンに分類し、ゾーン別の空間計画戦略を提案しており、生態系に敏感な町における低炭素空間計画に定量的根拠を提供する。
English
This study develops a detailed carbon accounting inventory and spatial efficiency evaluation framework for Fuqiushan Township, China. It visualizes emissions and sinks, creates composite efficiency indices, and classifies the area into five low-carbon development zones with tailored spatial planning 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
中国の町を事例とするが、日本の地方自治体におけるゼロカーボンシティ戦略や土地利用計画にも応用可能なフレームワーク。特に炭素排出・吸収の空間可視化とゾーニング手法は、日本の「脱炭素先行地域」選定などに示唆を与える。
In the global GX context
While focused on a Chinese case, this study offers a spatially explicit carbon accounting and efficiency methodology applicable to township-level low-carbon planning globally. The zoning approach integrating emissions sources and carbon sinks is relevant for ecologically sensitive rural areas worldwide.
👥 読者別の含意
🔬研究者:Novel methodology for township-scale carbon accounting and spatial efficiency evaluation.
🏢実務担当者:Local planners can adopt the zoning strategy to design area-specific low-carbon measures.
🏛政策担当者:Provides a quantitative basis for integrating carbon goals into spatial planning at the township level.
📄 Abstract(原文)
Driven by the goal of carbon neutrality, low-carbon development in township spaces is essential for sustainable urban–rural growth. This paper employs a carbon accounting methodology, taking Fuqiushan Town in the Dongting Lake Ecological Economic Zone as a case study to develop a detailed carbon measurement inventory at the township scale. Using spatial analysis techniques, it synthesizes multi-source data—including land use, agricultural inputs, and population—to estimate emissions from key sources such as crop cultivation, livestock and poultry breeding, industrial production, and residential activities. The study also evaluates the carbon sequestration capacity of sinks such as woodlands and water bodies, enabling the spatial visualization of both carbon emissions and carbon sinks. Key findings include: (1) Fuqiushan Town exhibits a carbon emission profile characterized by “industrial activities as the primary source, supplemented by agriculture, with additional contributions from residential and transportation sectors,” while forested areas and water bodies serve as core carbon sink zones. (2) An innovative multidimensional indicator system for low-carbon development efficiency was established, consisting of the Low-Carbon Development Efficiency Index in Production, the Daily Life Carbon Responsibility Efficiency Index, and the Ecological Carbon Sink Efficiency Index, which together form a Comprehensive Efficiency Index for Low-Carbon Development. (3) Analysis reveals significant spatial coupling relationships and efficiency differentiation patterns among carbon emissions, industrial structure, energy dependence, and ecological background. Based on dominant carbon emission types, low-carbon efficiency thresholds, and spatial factor interactions, the 17 villages and one forest farm in the township are classified into five zones: “Industrial High-Carbon Transition Zone,” “Agricultural Pollution Reduction and Carbon Emission Reduction Synergy Zone,” “Ecological Low-Carbon Conservation Zone,” “Human Settlements Balanced Development Zone,” and “Ecological Core Zone.” Tailored low-carbon spatial planning strategies for material resources are proposed for each zone. These results offer quantitative support and spatially targeted insights for low-carbon spatial planning in ecologically sensitive townships, contributing to the achievement of objectives such as “carbon reduction and sink increase” and “rural revitalization.”
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://www.mdpi.com/2071-1050/18/7/3470/pdf?version=1775125448first seen 2026-07-24 06:59:21
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