A comparison of chamber-based methods for measuring N2O emissions from arable soils

IF 5.6 1区 农林科学 Q1 AGRONOMY
Meng Kong , Farhana Ferdous Mitu , Søren O. Petersen , Poul Erik Lærke , Diego Abalos , Peter Sørensen , Andreas Brændholt , Sander Bruun , Jørgen Eriksen , Christian Dold
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引用次数: 0

Abstract

Static chamber-based flux measurements with gas chromatography are commonly used to estimate nitrous oxide (N2O) emissions from arable soils. The LI-COR 7820 N2O/H2O (LI-7820) enables higher-frequency in situ measurements, but side-by-side comparisons with traditional methods are limited. To address this gap, we compared non-steady-state chamber methods including non-flow-through (NFT) and flow-through (FT) chamber methods under field and laboratory conditions with plant cover or bare soil. The LI-7820 was used with the LI-8200S smart chamber (FT-1: ⌀ 20 cm) and a self-built chamber (FT-2: 60 × 60 cm), and compared to differently sized NFTs (1–4: 75 × 75, 27 × 37, 60 × 60, and ⌀ 20 cm) with manual sampling with gas chromatography. Field experiments showed high RMSE for daily N2O fluxes within 20 days after fertilizer application between FT-1 and NFTs, particularly for maize and spring barley (183 and 214 μg N2O-N m−2 h−1), which dropped sharply after 20 days (47 and 54 μg N2O-N m−2 h−1, respectively). FT-2 and NFT-3 for pastures had lower RMSE and MAE, both below 40 μg N2O-N m−2 h−1. In the incubation experiment, bare soil showed smaller error values, remaining below 26 μg N2O-N m−2 h−1. Significant differences were observed between the cumulative N2O emissions measured with NFTs and FT-1, while differences were not significant between NFT-3 and FT-2. Several factors may explain these differences. The smaller chamber dimensions of FT-1 may influence water and nitrogen distribution and constrain the capture of spatial heterogeneity, while NFTs could be affected by prolonged deployment times and in-chamber pressure changes. Furthermore, the lack of water-vapor correction in NFTs, unlike the LI-7820, contributed to discrepancies between methods. Understanding these nuances including the impact of the chamber design, is essential for enhancing the comparability of N2O emissions and getting closer to achieving unbiased measurements of the true flux.
基于室内的测量耕地土壤N2O排放方法的比较
静态室通量测量与气相色谱法通常用于估计一氧化二氮(N2O)排放的耕地土壤。LI-COR 7820 N2O/H2O (LI-7820)可实现更高频率的原位测量,但与传统方法的并排比较受到限制。为了解决这一差距,我们在植物覆盖或裸露土壤的野外和实验室条件下比较了非稳态室方法,包括非流过(NFT)和流过(FT)室方法。LI-7820与LI-8200S智能室(FT-1: 20 cm)和自建室(FT-2: 60 × 60 cm)一起使用,并与不同尺寸的nft (1-4: 75 × 75、27 × 37、60 × 60和20 cm)进行气相色谱人工取样比较。田间试验表明,施肥后20天内,玉米和春大麦的日N2O通量RMSE较高(分别为183和214 μg N2O- n m−2 h−1),20天后RMSE急剧下降(分别为47和54 μg N2O- n m−2 h−1)。牧场的FT-2和NFT-3的RMSE和MAE较低,均低于40 μg N2O-N m−2 h−1。在培养实验中,裸土的误差值较小,保持在26 μg N2O-N m−2 h−1以下。nft -1和NFT-3测量的累积N2O排放量之间存在显著差异,而NFT-3和FT-2之间差异不显著。有几个因素可以解释这些差异。FT-1较小的腔室尺寸可能会影响水和氮的分布,并限制空间异质性的捕获,而nft可能会受到长时间部署时间和腔内压力变化的影响。此外,与LI-7820不同,nft中缺乏水蒸气校正,导致了方法之间的差异。了解这些细微差别,包括室设计的影响,对于增强N2O排放的可比性和更接近于实现对真实通量的无偏测量至关重要。
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来源期刊
CiteScore
10.30
自引率
9.70%
发文量
415
审稿时长
69 days
期刊介绍: Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published. Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.
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