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\begin{document}

\title{New Open-Path Low-Power Standardized Automated CO2/H2O Flux Measurement
System: Concentrations, Co-spectra and Fluxes Comparison with
Established Models}



\author[1]{George Burba}%
\author[2]{Israel Begashaw}%
\author[2]{James Kathilankal}%
\affil[1]{Affiliation not available}%
\affil[2]{LI-COR Biosciences}%


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  \date{May 24, 2024}


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\selectlanguage{english}
\begin{abstract}
Spatial and temporal flux data coverage have improved significantly in
recent years, due to standardization, automation and management of data
collection, and better handling of the generated data. With more
stations and networks, larger data streams from each station, and
smaller operating budgets, modern tools are required to effectively and
efficiently handle the entire process. These tools should produce
standardized verifiable datasets, and provide a way to cross-share the
standardized data with external collaborators to leverage available
funding, and promote data analyses and publications. In 2015, new
open-path and enclosed flux measurement systems1 were developed, based
on established gas analyzer models2,3, with the goal of improving
stability in the presence of contamination over older models4, refining
temperature control and compensation5,6, providing more accurate gas
concentration measurements1, and synchronizing analyzer and anemometer
data streams in a very careful manner7. In late 2017, the new open-path
system was further refined to simplify hardware configuration, to
significantly reduce power consumption and cost, and to prevent or
considerably minimize flow distortion8 in the anemometer to increase
data coverage. Additionally, all new systems incorporate complete
automated on-site flux calculations using EddyPro\selectlanguage{ngerman}® Software9 run by a
weatherized remotely-accessible microcomputer to provide standardized
traceable data sets for fluxes and supporting variables. This
presentation will describe details and results from the latest field
tests of the new flux systems, in comparison to older models and control
reference instruments. References: 1 Burba G., W. Miller, I. Begashaw,
G. Fratini, F. Griessbaum, J. Kathilankal, L. Xu, D. Franz, E. Joseph,
E. Larmanou, S. Miller, D. Papale, S. Sabbatini, T. Sachs, R. Sakai, D.
McDermitt, 2017. Comparison of CO2 Concentrations, Co-spectra and Flux
Measurements between Latest Standardized Automated CO2/H2O Flux Systems
and Older Gas Analysers. 10th ICDC Conference, Switzerland: 21-25/08 2
Metzger, S., G. Burba, S. Burns, P. Blanken, J. Li, H. Luo, R. Zulueta,
2016. Optimization of an enclosed gas analyzer sampling system for
measuring eddy covariance fluxes of H2O and CO2. AMT, 9: 1341-1359 3
Burba, G., 2013. Eddy Covariance Method for Scientific, Industrial,
Agricultural and Regulatory Applications. LI-COR Biosciences: 331 pp. 4
Fratini, G., McDermitt, D.K. and Papale, D., 2014. Eddy-covariance flux
errors due to biases in gas concentration measurements: origins,
quantification and correction. Biogeosciences, 11(4), pp.1037-1051. 5
McDermitt, D., J. Welles, and R. Eckles, 1993. Effects of temperature,
pressure, and water vapor on gas phase infrared absorption by CO2.
LI-COR, Inc. Lincoln, NE. 6 Welles, J. and D. McDermitt, 2005. Measuring
carbon dioxide in the atmosphere. In: Hatfield J. and J. Baker (Eds.)
Micrometeorology in Agricultural Systems. ASA-CSSA-SSSA, Madison, W%
\end{abstract}\selectlanguage{ngerman}%



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