High-precision measurements of the methane flux over a larch forest based on a hyperbolic relaxed eddy accumulation method using a laser spectrometer

Ueyama, Masahito; Takai, Yuriko; Takahashi, Yoshiyuki; Ide, Reiko; Hamotani, Ken; Kosugi, Yukio; Takahashi, Kenshi; Saigusa, Nobuko

doi:10.1016/j.agrformet.2013.04.029

Cited by 11 publications

(39 citation statements)

References 48 publications

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“…These methods can quantify spatially representative fluxes, which was often difficult to accomplish with chamber methods due to the large spatial variability in CH 4 fluxes (Itoh et al, 2009). At the same time, there is uncertainty associated with micrometeorological CH 4 flux due to an analyzer's precision (Sakabe et al, 2012;Ueyama et al, 2013;Wang et al, 2013), resulting in small statistical powers in relation to environmental variables. Simultaneous studies using both micrometeorological and chamber methods could be a powerful tool to evaluate CH 4 fluxes in upland forests Wang et al, 2013); but comparisons for each method have rarely been conducted.…”

Section: Introductionmentioning

confidence: 99%

“…Micrometeorological techniques have become available for measuring small CH 4 fluxes in upland forests at the canopy scale (Sakabe et al, 2012;Ueyama et al, 2013Wang et al, 2013. These methods can quantify spatially representative fluxes, which was often difficult to accomplish with chamber methods due to the large spatial variability in CH 4 fluxes (Itoh et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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Methane uptake in a temperate forest soil using continuous closed-chamber measurements

Ueyama

Takeuchi

Takahashi

et al. 2015

Agricultural and Forest Meteorology

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Methane uptake in a temperate forest soil using continuous closed-chamber measurements

Ueyama

Takeuchi

Takahashi

et al. 2015

Agricultural and Forest Meteorology

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“…This analyzer was capable of measuring H 2 O, CO 2 , and CH 4 simultaneously, with high precision. Characteristics of this analyzer have been reported in previous studies (Baer et al, 2002;Sakabe et al, 2012;Ueyama et al, 2013;Iwata et al, 2014). We also attached a dehumidifier unit (MD-110-72F, PermaPure, USA) in the sampling line, immediately before the inlet of the analyzer.…”

Section: Definition and Practice Of Dilution By Water Vapor And Corrmentioning

confidence: 99%

“…Recent improvements in sensor technology now allow the simultaneous measurement of concentrations or mixing ratios of H 2 O and targeted trace gas in-situ at field sites. Simultaneous measurements using current analyzers have resulted in rather accurate CH 4 -fluxes at a rice paddy and at forest sites Ueyama et al, 2013). These studies employed Nafion dryers as pre-drying units to control humidity and minimize influence on the spectral line shape of CH 4 (Tuzson et al, 2010;Nara et al, 2012).…”

Section: Definition and Practice Of Dilution By Water Vapor And Corrmentioning

confidence: 99%

“…Major environmental variables measured were short-and longwave radiation (incoming and reflection, CNR4, Kipp & Zonen, the Netherlands), photosynthetically active radiation (incoming and reflection, LI-190, LiCor, USA), wind profile (four heights, AF750, Makino, Japan), temperature and humidity (four heights, HMP41, Vaisala, Finland), atmospheric pressure (PTB110, Vaisala, Finland), soil heat fluxes (five locations, MF-8, Eko, Japan), soil temperature (five depths, thermocouples), and soil volumetric water content (CS616, Campbell Scientific Inc., USA). Further information details regarding the UAF-site and its micrometeorology are available in previous publications (Ueyama et al, 2006a(Ueyama et al, , 2009(Ueyama et al, , 2013(Ueyama et al, , 2014Ueyama and Harazono, 2007;Kim et al, 2007;Iwata et al, 2010Iwata et al, , 2012. 3.2 Chamber and analyzer employed at UAF-site Gas analyzer: We applied a laser-based analyzer (FGGA907, LGR, USA) for chamber measurements in slow-mode, using an internal pump with a sampling flow rate of 0.65 L min -1 .…”

Section: Definition and Practice Of Dilution By Water Vapor And Corrmentioning

confidence: 99%

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Effects of water vapor dilution on trace gas flux, and practical correction methods

Harazono

Iwata

Sakabe

et al. 2015

J. Agric. Meteorol.

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The effect of water vapor dilution on CH 4 flux was examined here using dynamic chamber measurements at the forest floor of a black spruce forest in interior Alaska. CH 4 and CO 2 concentrations were differently diluted by increased water vapor in each chamber. After correction for water vapor dilution was applied, source (positive) CH 4 flux was enhanced, whereas sink (negative) flux was reduced, and magnitude changed depending on the condition of water vapor.Several methods were examined to practically correct water vapor dilution for fluxes previously measured. Numerical correction for all data sampled at high frequency intervals (DAE-method) is highly recommended. Water vapor dilution correction for ensemble-averaged data (SA-method) is also applicable, though not recommended in case of long-term average data for accurate flux determination, especially for data obtained at irregular source strength plots. When evapotranspiration is measured in parallel to CH 4 flux, the removal of the water vapor increment due to evapotranspiration in the chamber is another option for correction (HCE-method). This method resulted in similar accuracy to the DAEmethod, as long as continuously sampled data were applicable.The application of the correction for water vapor dilution to previous tower-based flux data (measured over a wet sedge tundra in Barrow throughout the month of August, 2000) also resulted in an increase in source (positive) flux of 6.6% on average.This study concludes that either accurate flux must be determined using mixing ratio, or a water vapor dilution correction must be applied using simultaneously measured water vapor and trace gases.

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Inferring methane fluxes at a larch forest using Lagrangian, Eulerian, and hybrid inverse models

2014

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Measuring methane (CH 4 ) flux at upland forests is challenging due to high levels of heterogeneity in upscaling chamber measurements and the detection limits of currently available micrometeorological methods. We estimated CH 4 fluxes in an upland forest from vertical concentration profiles using three different inverse multilayer models: the Lagrangian localized near field theory, Eulerian, and hybrid Lagrangian-Eulerian models. The approach could estimate spatially representative fluxes, and use of higher gradients within canopies than above them could minimize uncertainties associated with sensor noises. Comparing fluxes by the models and measurements by the micrometeorological hyperbolic relaxed eddy accumulation and chamber methods, daytime fluxes were reasonably reproduced, but nighttime fluxes were overestimated most likely due to an underestimation of stable conditions and storage effects. The models and measurements show that the forest acted as a CH 4 sink during the study period, and the soil acted as the dominant sink. The estimated sink increased with increasing soil temperatures and decreasing soil water content. The CH 4 sink estimated during the study period were 1.5 ± 0.2 nmol m À2 s À1 by the micrometeorological method, 2.4 ± 0.5 nmol m À2 s À1 by chambers, 2.8 ± 1.1 nmol m À2 s À1 by the Lagrangian model, 2.7 ± 1.0 nmol m À2 s À1 by the Eulerian model, and 3.7 ± 2.8 nmol m À2 s À1 by the hybrid model. The performance of the Lagrangian and hybrid models increased when the CH 4 sink/source was assumed to only exist in the soil.

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High-precision measurements of the methane flux over a larch forest based on a hyperbolic relaxed eddy accumulation method using a laser spectrometer

Cited by 11 publications

References 48 publications

Methane uptake in a temperate forest soil using continuous closed-chamber measurements

Methane uptake in a temperate forest soil using continuous closed-chamber measurements

Effects of water vapor dilution on trace gas flux, and practical correction methods

Inferring methane fluxes at a larch forest using Lagrangian, Eulerian, and hybrid inverse models

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