Measuring fluxes of trace gases and energy between ecosystems and the atmosphere - the state and future of the eddy covariance method

2014 ◽  
Vol 20 (12) ◽  
pp. 3600-3609 ◽  
Author(s):  
Dennis Baldocchi
Keyword(s):  
Eddy Covariance ◽  
Trace Gases ◽  
The State ◽  
Eddy Covariance Method

scholarly journals Measurements of nitrogen oxides and ozone fluxes by eddy covariance at a meadow: evidence for an internal leaf resistance to NO<sub>2</sub>

2013 ◽  
Vol 10 (9) ◽  
pp. 5997-6017 ◽  
Author(s):  
P. Stella ◽  
M. Kortner ◽  
C. Ammann ◽  
T. Foken ◽  
F. X. Meixner ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
A Priori ◽  
Terrestrial Ecosystems ◽  
Stomatal Resistance ◽  
Internal Resistance ◽  
Ozone Production ◽  
Deposition Flux ◽  
Eddy Covariance Method ◽  
Large Variability ◽  
Leaf Resistance

Abstract. Nitrogen dioxide (NO2) plays an important role in atmospheric pollution, in particular for tropospheric ozone production. However, the removal processes involved in NO2 deposition to terrestrial ecosystems are still the subject of ongoing discussion. This study reports NO2 flux measurements made over a meadow using the eddy covariance method. The measured NO2 deposition fluxes during daytime were about a factor of two lower than a priori calculated fluxes using the Surfatm model without taking into account an internal (also called mesophyllic or sub-stomatal) resistance. Neither an underestimation of the measured NO2 deposition flux due to chemical divergence or an in-canopy NO2 source nor an underestimation of the resistances used to model the NO2 deposition explained the large difference between measured and modelled NO2 fluxes. Thus, only the existence of the internal resistance could account for this large discrepancy between model and measurements. The median internal resistance was estimated to be 300 s m−1 during daytime, but exhibited a large variability (100–800 s m−1). In comparison, the stomatal resistance was only around 100 s m−1 during daytime. Hence, the internal resistance accounted for 50–90% of the total leaf resistance to NO2. This study presents the first clear evidence and quantification of the internal resistance using the eddy covariance method; i.e. plant functioning was not affected by changes of microclimatological (turbulent) conditions that typically occur when using enclosure methods.

scholarly journals Options to correct local turbulent flux measurements for large-scale fluxes using a LES-based approach

2021 ◽  
Author(s):  
Matthias Mauder ◽  
Andreas Ibrom ◽  
Luise Wanner ◽  
Frederik De Roo ◽  
Peter Brugger ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Large Scale ◽  
Heat Fluxes ◽  
Eddy Covariance Method ◽  
Boundary Layer Height ◽  
Secondary Circulations ◽  
Low Pass ◽  
Measurement Height ◽  
Flux Measurements ◽  
Dispersive Fluxes

Abstract. The eddy-covariance method provides the most direct estimates for fluxes between ecosystems and the atmosphere. However, dispersive fluxes can occur in the presence of secondary circulations, which can inherently not be captured by such single-tower measurements. In this study, we present options to correct local flux measurements for such large-scale transport based on a non-local parametric model that has been developed from a set of idealized LES runs for three real-world sites. The test sites DK-Sor, DE-Fen, and DE-Gwg, represent typical conditions in the mid-latitudes with different measurement height, different terrain complexity and different landscape-scale heterogeneity. Different ways to determine the boundary-layer height, which is a necessary input variable for modelling the dispersive fluxes, are applied, either from operational radio-soundings and local in-situ measurements for the flat site or from backscatter-intensity profile obtained from collocated ceilometers for the two sites in complex terrain. The adjusted total fluxes are evaluated by assessing the improvement in energy balance closure and by comparing the resulting latent heat fluxes with evapotranspiration rates from nearby lysimeters. The results show that not only the accuracy of the flux estimates is improved but also the precision, which is indicated by RMSE values that are reduced by approximately 50 %. Nevertheless, it needs to be clear that this method is intended to correct for a bias in eddy-covariance measurements due to the presence of large-scale dispersive fluxes. Other reasons potentially causing a systematic under- or overestimation, such as low-pass filtering effects and missing storage terms, still need to be considered and minimized as much as possible. Moreover, additional transport induced by surface heterogeneities is not considered.

scholarly journals Measurement of Air-Sea Methane Fluxes in the Baltic Sea Using the Eddy Covariance Method

2019 ◽  
Vol 7 ◽  
Author(s):  
Lucía Gutiérrez-Loza ◽  
Marcus B. Wallin ◽  
Erik Sahlée ◽  
Erik Nilsson ◽  
Hermann W. Bange ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Eddy Covariance ◽  
The Baltic Sea ◽  
Eddy Covariance Method ◽  
Methane Fluxes ◽  
The Baltic

Methane Emission Reductions from the Alternate Wetting and Drying of Rice Fields Detected Using the Eddy Covariance Method

2018 ◽  
Vol 53 (2) ◽  
pp. 671-681 ◽  
Author(s):  
Benjamin R. K. Runkle ◽  
Kosana Suvočarev ◽  
Michele L. Reba ◽  
Colby W. Reavis ◽  
S. Faye Smith ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Methane Emission ◽  
Rice Fields ◽  
Eddy Covariance Method ◽  
Wetting And Drying ◽  
Emission Reductions ◽  
Alternate Wetting And Drying

scholarly journals Air-Sea Fluxes of CO<sub>2</sub> and CH<sub>4</sub> from the Penlee Point Atmospheric Observatory on the South West Coast of the UK

2016 ◽  
Author(s):  
M. Yang ◽  
T. G. Bell ◽  
F. E. Hopkins ◽  
V. Kitidis ◽  
P. W. Cazenave ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
West Coast ◽  
Phytoplankton Bloom ◽  
Flux Measurement ◽  
Sensible Heat ◽  
The South ◽  
Eddy Covariance Method ◽  
Spring Phytoplankton Bloom ◽  
South West ◽  
South West Coast

Abstract. We present air-sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the South West coast of the United Kingdom. Measurements from the southwest direction (background marine air) at three different sampling heights (approximately 15, 18, 27 m above mean sea level, AMSL) in three different periods during 2014–2015 are shown. At sampling heights ≥ 18 m AMSL, measured fluxes of momentum and sensible heat demonstrate reasonable agreement with their expected transfer rates over the open ocean. This confirms the suitability of PPAO for air-sea exchange measurements. We observed reductions in the air-to-sea fluxes of CO2 from spring to summer in both years, which coincided with the breakdown of the spring phytoplankton bloom. At all sampling heights, mean CH4 fluxes were positive, suggesting marine emissions. Higher CH4 fluxes were observed during rising tides (20&amp;pm;3; 29&amp;pm;6; 38&amp;pm;3 μmole m−2 d−1 at 15, 27, 18 m AMSL) than during falling tides (14&amp;pm;2; 21&amp;pm;5; 22&amp;pm;2 μmole m−2 d−1, respectively), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. Based on observations at PPAO, we also estimate the detection limit of the eddy covariance CH4 flux measurement to be ~20 μmole m−2 d−1 over hourly timescales (~4 μmole m−2 d−1 over 24 hours).

scholarly journals Estimation of Carbon Fluxes from Eddy Covariance Data and Satellite-Derived Vegetation Indices in a Karst Grassland (Podgorski Kras, Slovenia)

2019 ◽  
Vol 11 (6) ◽  
pp. 649 ◽  
Author(s):  
Koffi Noumonvi ◽  
Mitja Ferlan ◽  
Klemen Eler ◽  
Giorgio Alberti ◽  
Alessandro Peressotti ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Eddy Covariance ◽  
Vegetation Index ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Information Criterion ◽  
Growing Season ◽  
Coefficient Of Determination ◽  
Regression Equations ◽  
Eddy Covariance Method

The Eddy Covariance method (EC) is widely used for measuring carbon (C) and energy fluxes at high frequency between the atmosphere and the ecosystem, but has some methodological limitations and a spatial restriction to an area, called a footprint. Remotely sensed information is usually used in combination with eddy covariance data in order to estimate C fluxes over larger areas. In fact, spectral vegetation indices derived from available satellite data can be combined with EC measurements to estimate C fluxes outside of the tower footprint. Following this approach, the present study aimed to model C fluxes for a karst grassland in Slovenia. Three types of model were considered: (1) a linear relationship between Net Ecosystem Exchange (NEE) or Gross Primary Production (GPP) and each vegetation index; (2) a linear relationship between GPP and the product of a vegetation index with PAR (Photosynthetically Active Radiation); and (3) a simplified LUE (Light Use-Efficiency) model assuming a constant LUE. We compared the performance of several vegetation indices derived from two remote platforms (Landsat and Proba-V) as predictors of NEE and GPP, based on three accuracy metrics, the coefficient of determination (R2), the Root Mean Square Error (RMSE) and the Akaike Information Criterion (AIC). Two types of aggregation of flux data were explored: midday average and daily average fluxes. The vapor pressure deficit (VPD) was used to separate the growing season into two phases, a wet and a dry phase, which were considered separately in the modelling process, in addition to the growing season as a whole. The results showed that NDVI is the best predictor of GPP and NEE during the wet phase, whereas water-related vegetation indices, namely LSWI and MNDWI, were the best predictors during the dry phase, both for midday and daily aggregates. Model 1 (linear relationship) was found to be the best in many cases. The best regression equations obtained were used to map GPP and NEE for the whole study area. Digital maps obtained can practically contribute, in a cost-effective way to the management of karst grasslands.

scholarly journals Some aspects of the energy balance closure problem

2006 ◽  
Vol 6 (12) ◽  
pp. 4395-4402 ◽  
Author(s):  
T. Foken ◽  
F. Wimmer ◽  
M. Mauder ◽  
C. Thomas ◽  
C. Liebethal
Keyword(s):  
Surface Layer ◽  
Energy Balance ◽  
Eddy Covariance ◽  
Low Frequency ◽  
Turbulent Fluxes ◽  
Closure Problem ◽  
Energy Balance Closure ◽  
Considerable Influence ◽  
Turbulence Spectrum ◽  
Eddy Covariance Method

Abstract. After briefly discussing several reasons for the energy balance closure problem in the surface layer, the paper focuses on the influence of the low frequency part of the turbulence spectrum on the residual. Changes in the turbulent fluxes in this part of the turbulence spectrum were found to have a significant influence on the changes of the residual. Using the ogive method, it was found that the eddy-covariance method underestimates turbulent fluxes in the case of ogives converging for measuring times longer than the typical averaging interval of 30 min. Additionally, the eddy-covariance method underestimates turbulent fluxes for maximal ogive functions within the averaging interval, both mainly due to advection and non-steady state conditions. This has a considerable influence on the use of the eddy-covariance method.

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