Quantifying temporal dynamics of greenhouse gas emissions in lake mesocosms: Deployment of a low‐cost measurement system
湖沼メソコスムにおける温室効果ガス排出の時間的動態の定量化：低コスト測定システムの展開 (AI 翻訳)
Tuba Bucak, Eti Ester Levi, Claus Melvad, Jianming Deng, Mikhail Mastepanov, Robert Ladwig, Thomas Alexander Davidson
🤖 gxceed AI 要約
日本語
本研究は、デンマークの湖沼メソコスム実験において、低コスト・高頻度のGHG測定システムを7ヶ月間運用し、CO2とCH4フラックスの時間変動を定量化した。CH4では泡立ちによる排出が支配的で大きな変動が見られ、CO2と溶存CH4には顕著な日周変動が観察された。サンプリング間隔を週1回にすることで、月1回よりも不確実性を低減できることが示された。
English
This study deployed a low-cost, high-frequency GHG measurement system in lake mesocosms in Denmark over 7 months, quantifying temporal variability of CO2 and CH4 fluxes. Ebullitive CH4 dominated with large variation, and diurnal fluctuations were significant for CO2 and diffusive CH4. Weekly sampling reduced uncertainty compared to monthly intervals.
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
本論文は、湖沼からのGHG排出測定手法の改善に貢献するもので、日本の湖沼研究や環境アセスメントにも応用可能な知見を提供する。ただし、企業のGX実務や日本の制度との直接的な関連は薄い。
In the global GX context
This paper advances freshwater GHG measurement methodology, highlighting the importance of high-frequency data and diurnal cycle consideration. While not directly tied to corporate disclosure, it underpins the scientific basis for emission inventories and natural climate solutions.
👥 読者別の含意
🔬研究者:High-frequency measurement techniques and sampling optimization for lake GHG fluxes are valuable for improving emission estimates and reducing upscaling uncertainty.
📄 Abstract（原文）
Abstract Greenhouse gas (GHG) emissions from freshwater ecosystems contribute significantly to global carbon budgets, yet they remain poorly constrained due to limited high‐frequency measurements. We tested a low‐cost, high‐frequency GHG measurement system in a long‐term mesocosm experiment in Lemming, Denmark, over a 7‐month period, focusing on CO 2 and CH 4 fluxes. We deployed a methodology for calculating CH 4 diffusive fluxes using high‐frequency sensor data and tested the effects of sampling intervals on emission upscaling. Our findings reveal substantial temporal variability in GHG emissions, particularly for CH 4 , with ebullitive fluxes dominating and exhibiting large variation. Pronounced diurnal fluctuations were also observed for CO 2 and diffusive CH 4 fluxes, whereas ebullitive CH 4 emissions showed no significant diurnal pattern. Relying solely on daytime measurements led to a significant overestimation of overall CO 2 fluxes and CH 4 diffusive fluxes. Resampling data at lower frequency showed that reduced sampling frequency leads to an underestimation of total emissions, especially for CH 4 ebullitive fluxes. Increasing the sampling interval from daily to monthly markedly increased uncertainty, while weekly sampling better captured overall GHG flux patterns and reduced the uncertainty compared with more infrequent sampling. These results underscore the value of high‐frequency GHG measurements in capturing both diurnal and seasonal variations, improving the accuracy of flux estimates, and reducing uncertainties in upscaling emission. We emphasize the need to optimize sampling intervals and incorporate diurnal cycle measurements to enhance the accuracy and reliability of freshwater GHG assessments.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.1002/lom3.70060first seen 2026-05-14 22:42:51
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。