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高標高都市・西寧における炭素効率の高い都市木本植物のスクリーニング:季節的光合成動態と林冠炭素固定ポテンシャル

Screening carbon‑efficient urban woody plants in high‑altitude Xining: seasonal photosynthetic dynamics and canopy carbon‑sequestration potential (原題)

Huilin Yang, Yitong Zhang, Qiutan Ren, Xiaoyang Tan, Hengjia Zhang, Qingyang Wang, YanXia JIN, Qirui Wang, Jiankang Ling, Zhijun Liu, Ang Li, Yangyang Zhang, Xiaoqin Liu, Ho Yi Wan, Cao Hui, Zhe Chen, Hanyue Zhu, Zheng Wang, Shidong Ge, Xufeng Mao

Trees Forests and People📚 査読済 / ジャーナル2026-08-30#気候科学Origin: CN対象セクター: construction
DOI: 10.1016/j.tfp.2026.101476
原典: https://doi.org/10.1016/j.tfp.2026.101476
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🤖 gxceed AI 要約

日本語

中国・西寧(標高2,261m)の都市緑地16地点で、一般的に植栽される木本植物106種(樹木58種・低木48種)を対象に、2025年生育期の純光合成速度と林冠CO₂固定ポテンシャルを推定した。平均光合成速度は7月にピーク(9.49 µmol m⁻² s⁻¹)を示す一山型の季節変動をとり、落葉広葉樹が常緑針葉樹を上回った。樹種・生活形間の差は大きく、公園・道路・住宅地ごとの植栽テンプレートを提案している。

English

Across 106 urban woody species (58 trees, 48 shrubs) at 16 green-space sites in Xining, China (2,261 m a.s.l.), seasonal net photosynthesis and growing-season canopy CO2 assimilation potential were quantified. Mean Pn peaked in July (9.49 µmol m-2 s-1) with a unimodal pattern, and deciduous broad-leaved species generally outperformed evergreen conifers. Five performance classes support site-specific planting templates for parks, roads and residential areas, though multi-year monitoring and life-cycle accounting remain pending.

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

日本でも都市緑地の炭素吸収は自治体の脱炭素計画やJ-クレジット(森林・緑地)に関連しうるが、本論文は中国の単一都市・単年データであり、SSBJ・有報・統合報告書といった企業開示への直接の示唆は限定的。都市緑化の炭素評価手法(i-Tree Eco併用、葉面積推定)は日本の自治体・造園実務の参考になりうる。

In the global GX context

Urban green-space carbon accounting sits adjacent to, but outside, the core TCFD/ISSB/CSRD disclosure architecture; it speaks more to municipal climate action and nature-based carbon removal than to corporate transition finance. The species-level screening approach and i-Tree Eco integration offer a transferable method for cities seeking to quantify green-infrastructure carbon co-benefits.

👥 読者別の含意

🔬研究者:高標高・寒冷都市における樹種別炭素固定ポテンシャルの実測ベースラインと、葉面積推定を組み合わせた評価手法を提供する。

🏢実務担当者:都市緑化・造園計画において、炭素性能と空気質・熱快適性を両立させる樹種選定の参考になる。

🏛政策担当者:自治体の緑地整備計画や都市炭素吸収量の把握に、樹種別・空間別のスクリーニング手法を応用できる。

📄 Abstract(原文)

Urban green spaces are increasingly expected to support municipal carbon mitigation, yet species-level evidence remains scarce for high-altitude cold cities. We quantified seasonal net photosynthetic rate (Pₙ) and estimated growing-season canopy CO₂ assimilation potential for 106 commonly planted urban woody species (58 trees and 48 shrubs) across sixteen urban green-space sites in Xining, China (2,261 m a.s.l.), during the 2025 growing season (May–October). Monthly diurnal Pₙ measurements were integrated with total leaf area estimates derived from field structural measurements, i-Tree Eco leaf-area parameters and shrub-specific allometric models. Across species, mean Pₙ generally followed a unimodal seasonal pattern, peaking in July at 9.49 ± 0.21 μmol m⁻² s⁻¹, with lower rates in spring and autumn. Estimated growing-season canopy CO₂ assimilation potential varied strongly among taxa and life forms. Ulmus pumila reached the highest value among trees (146.48 ± 33.71 CO₂ yr⁻¹), followed by Populus alba and Populus cathayana , whereas Hippophae rhamnoides ranked highest among shrubs (0.852 ± 0.152 kg CO₂ yr⁻¹), followed by Elaeagnus angustifolia and Ligustrum sinense . Deciduous broad-leaved species generally outperformed evergreen conifers, suggesting that high peak-season assimilation and large leaf area can outweigh longer leaf retention under a short growing season. Clustering grouped trees and shrubs into five performance classes, supporting site-specific planting templates for parks, roads and residential spaces that couple carbon performance with air-quality, thermal-comfort and amenity co-benefits. These results provide a one-growing-season screening baseline for carbon-efficient urban woody plant selection in Xining, pending multi-year monitoring, leaf-area validation and life-cycle carbon accounting.

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