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Significance of Greenhouse Gas Measurement for Carbon Management Technologies
Published in Subhas K Sikdar, Frank Princiotta, Advances in Carbon Management Technologies, 2020
The eddy covariance technique is based on the measurement of atmospheric turbulence properties. A fundamental assumption is that of homogenous and fully turbulent atmospheric transport in the region of interest at and near the surface. Primarily driven by circular eddy structures in the lower atmosphere, these eddies transport atmospheric constituents primarily horizontally but with vertical components that carry gases or energy from the surface into the PBL via a constant flux layer. Mathematically the vertical flux, or net ecosystem exchange, F (in units of mol m−2 s−1), can be represented as the covariance of the vertical velocity and dry air molar density of the species of interest, e.g., CO2 (Burba, 2013; Gu, 2012). F≈cd¯w′s′¯
Greenhouse Gases
Published in Lisamarie Windham-Myers, Stephen Crooks, Tiffany G. Troxler, A Blue Carbon Primer, 2018
The value of eddy covariance approaches is that they directly measure the flux of greenhouse gases between an ecosystem and the atmosphere with few disturbances to the ecosystem. In contrast to missing spatial and temporal patterns by using chambers, eddy covariance integrates greenhouse gas fluxes over an extended spatial footprint (up to hundreds of meters in length) and collects data over days, weeks, months, or even years. There are, however, limitations of this approach – including issues with integrating spatially patchy greenhouse gases (like CH4 and N2O); requirements of certain site conditions (size and horizontal homogeneity); and challenges with measurements at night (Baldocchi 2014; Chuang et al. 2016). In addition to these technical limitations, the use of eddy covariance approaches requires relatively expensive equipment and a particular computational and quantitative skill set that exceeds the requirements of chamber measurements.
Smart Sensors for Digital Agriculture
Published in Indu Bala, Kiran Ahuja, Harnessing the Internet of Things (IoT) for a Hyper-Connected Smart World, 2023
The eddy covariance method is a vital atmospheric measurement technique to determine vertical turbulent fluxes for given atmospheric boundary layers. It estimates heat, momentum, water vapor and gas fluxes typically carbon dioxide and methane. These utilize the surface atmospheric energy flux values for determining the exchange of water vapors, methane, carbon dioxide, oxygen, or other gases. The close chamber method could be used [60]. However, these sensors are preferred owing to continuous flux measuring capability with a greater precision.
Selected breakpoints of net forest carbon uptake at four eddy-covariance sites
Published in Tellus B: Chemical and Physical Meteorology, 2021
Thomas Foken, Wolfgang Babel, J. William Munger, Tiia Grönholm, Timo Vesala, Alexander Knohl
The net ecosystem exchange (NEE) was calculated as the sum of the eddy-covariance carbon dioxide flux and the change of the carbon dioxide storage in the air column below the sensor. The gap filling of the NEE data (Falge et al., 2001) was performed for respiration with the Lloyd-Taylor function (Lloyd and Taylor, 1994) and for assimilation with the Michaelis-Menten type function (Michaelis and Menten, 1913). These methods were also applied to calculate Gross Primary Production (GPP) and respiration (Res). Gaps in evapotranspiration (ET) measurements have been filled with a regression to the Priestley-Taylor potential evaporation (Priestley and Taylor, 1972). For the following analysis, the annual mean data or sums used are based on the FLUXNET database or the given publications (Table 1).
Multi-angular instrument for tower-based observations of canopy sun-induced chlorophyll fluorescence
Published in Instrumentation Science & Technology, 2020
Shuren Chou, Bin Chen, Jing M. Chen
In this study, we designed a tower-based system for multi-angular SIF measurements. This system includes two spectrometers (Ocean Optics HR4000) which have high light throughput and spectral resolution.[29] This system was used to measure SIF at four viewing zenith angles (VZA= 32°, 42°, 52°, and 62°) with eleven viewing azimuth angles (VAA = 30°, 60°, 90°, 120°, 150°, 180°, 210°, 240°, 300°, 330°, and 360°). Also, the following assumptions were made: (i) the underlying surface was spatially homogeneous so that measurements obtained from different areas of the canopy in different directions could be taken as those obtained from the same area in different directions and (ii) the field of view (FOV) was large enough so that the footprint of the observation from each angle represented the average condition of the entire canopy. This new multi-angular SIF instrument has been mounted with the eddy covariance (EC) flux tower at a paddy rice field.
Continuous flow hygroscopicity-resolved relaxed eddy accumulation (Hy-Res REA) method of measuring size-resolved sodium chloride particle fluxes
Published in Aerosol Science and Technology, 2018
N. Meskhidze, T. M. Royalty, B. N. Phillips, K. W. Dawson, M. D. Petters, R. Reed, J. P. Weinstein, D. A. Hook, R. W. Wiener
Sodium chloride particle fluxes measured by REA technique were intercompared against the eddy covariance (EC) turbulent flux measurements. A linear relationship was found for the flux values measured with the different techniques. Using the ratio of the two fluxes, the factor was derived, which agreed favorably with the value calculated through theoretical formulations. Overall, this study showed that the instrument resulted in unbiased particle flux measurements with the NaCl detection limit of 3 × 105 and classification limit of 6 × 105 m−2 s−1. The data analysis shows that when the instrument is tuned to measure NaCl particle fluxes (i.e., using a κ ∼ 1.3), the Hy-Res REA technique is able to achieve an order of magnitude separation between the NaCl and AS particle fluxes of similar magnitude. The NaCl detection limit of the instrument is within the range of current parameterizations estimates for 100 nm dry NaCl particles production flux from 3 × 104 to 2 × 106 m−2 s−1 for the near surface (U10) wind speed of 8 m s−1 (Lewis and Schwartz 2004; de Leeuw et al. 2011).