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Preliminary Assessment of Measurement Frequency and Replication Effects on Season-Long Greenhouse Gas Emissions and Global Warming Potential Estimation Consistency Among Various Ecosystems

様々な生態系における季節全体の温室効果ガス排出量と地球温暖化係数推定の一貫性に及ぼす測定頻度と反復の影響の予備的評価 (AI 翻訳)

Kristofor R. Brye, Diego Della Lunga, Jonathan B. Brye, Cassie Seuferling, Tyler Buchanan, Will Dockery, Lauren Gwaltney

Gases📚 査読済 / ジャーナル2026-07-06#気候科学Origin: US対象セクター: agriculture
DOI: 10.3390/gases6030032
原典: https://doi.org/10.3390/gases6030032

🤖 gxceed AI 要約

日本語

本研究は、様々な生態系(牧草地、プレーリー、大豆・綿花圃場)において、測定頻度(毎週、隔週、3週ごと)と反復数(3~5)が季節全体のCO2、CH4、N2O排出量および地球温暖化係数(GWP)推定の一貫性に与える影響を評価した。結果は、測定頻度や反復数によって推定値が有意に異なることを示し、信頼性の高い全圃場排出量推定には適切な測定設計が不可欠であることを明らかにした。

English

This field study evaluated how measurement frequency (weekly, biweekly, every third week) and replication (3-5) affect season-long CO2, CH4, and N2O emissions and global warming potential (GWP) estimates across multiple ecosystems including pasture, prairie, soybean, and cotton fields. Results show that estimates can vary significantly with measurement frequency and replication, highlighting the need for appropriate sampling design to reliably quantify whole-field emissions.

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

日本でも農業分野からのGHG排出量算定が求められており、本研究成果は圃場レベルの実測データに基づく排出係数の精緻化に参考となる。特に水田や畑作地帯での測定プロトコル検討に寄与する可能性がある。

In the global GX context

This study provides empirical evidence on how measurement frequency and replication impact the accuracy of GHG flux estimates, which is crucial for improving national greenhouse gas inventories and verifying emission reductions in agricultural landscapes globally.

👥 読者別の含意

🔬研究者:Provides guidance on experimental design for field GHG measurements to improve accuracy of flux estimates.

🏢実務担当者:Useful for agricultural consultants and farm advisors designing on-farm GHG monitoring programs.

🏛政策担当者:Informs the development of measurement protocols for agricultural GHG reporting and carbon credit verification.

📄 Abstract(原文)

For soil processes that are known to be temporally dynamic, such as soil respiration, methanogenesis, and nitrification–denitrification, it is challenging to capture temporal variations with field-portable greenhouse gas (GHG) analyzers to provide the most accurate estimates of season-long GHG emissions and global warming potentials (GWPs). The objective of this field study was to evaluate the effects of measurement frequency (i.e., weekly, every other week, and every third week), replication (i.e., three, four, or five), and their interaction on the consistency of season-long carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions and GWP estimates across multiple ecosystems. Results are based on direct, in-field measurements with a field-portable gas analyzer. Field research was conducted throughout the 2024 growing season in a minimally grazed pasture, tallgrass prairie, soybean under conventional and conservation management practices, and cotton under conservation management in Arkansas, USA. Season-long CO2 emissions and GWP from the tallgrass prairie were 1.1 times (12%) greater from the weekly and every-other-week (16.9 and 17.0 Mg ha−1, respectively), which did not differ, than the every-third-week (14.2 and 14.2 Mg ha−1, respectively) measurement frequencies. Season-long CH4 emissions from the minimally grazed pasture and conservation-tilled soybean system were ≥7.5 times greater with four and five replications, which did not differ, than with three replications. Global warming potential in the conservation-tilled soybean (13.9 Mg ha−1) and conservation-tilled cotton (21.1 Mg ha−1) systems were ≥1.1 times (13%) greater with the every-third-week than with the weekly data set. Though this study was somewhat limited due the data sub-setting approach used, even using current, state-of-the-art, field-portable GHG analyzers, an appropriate in-field measurement frequency and number of spatial replications should be considered to reliably quantify whole-field, season-long GHG emissions and GWP estimates.

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