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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® 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

Eddy Covariance method has been actively used by expert micrometeorologists for over 30 years, covering 2155 stationary locations globally, and numerous mobile campaigns over land and water surfaces. Latest measurement technologies and automated processing software are rapidly expanding the use of the method to non-micrometeorological research. Regulatory and commercial uses of the method also increase year-by-year. Despite widening adoption of the method, academic investigators outside the area of micrometeorology and the majority of non-academic investigators are still not familiar enough with the proper implementation of the method required for conducting high-quality, reliable, traceable, and defensible measurements in their respective areas of interest. Although data collection and processing are now automated, the method still requires significant care to correctly design the experiment, set up the site, organize and analyze the large amount of data. Efforts of the flux networks (e.g., FluxNet, Ameriflux, Asiaflux, ICOS, NEON, OzFlux, etc.) have led to major progress in the standardization of the method. The project-specific workflow, however, is difficult to unify because various experimental sites and purposes of studies demand different treatments, and site-, measurement- and purpose-specific approaches. To address this situation, step-by-step instructions were created to introduce a novice to general principles, requirements, applications, processing and analysis steps of the conventional Eddy Covariance technique in the form of the free electronic resource, a 660-page textbook titled “Eddy Covariance Method for Scientific, Regulatory, and Commercial Applications”. The explanations are provided using easy-to-understand illustrations and real-life examples, and text is written in a non-technical language to be practically useful to those new to this field. Information is provided on theory of the method (including the state of methodology, basic derivations, practical formulations, major assumptions, sources of errors, error treatments, etc.), practical workflow (e.g., experiment design, implementation, data processing, quality control and analysis), data sharing and flux stations networking, key alternative methods, and the most frequently overlooked details.

N2O and CH4 soil flux studies traditionally consider certain time periods and certain ecosystems to be of low importance due to very small or negligible expected flux rates. Periods of such “negligible” fluxes are rarely reported because small fluxes are hard to resolve, measurements are costly, time-consuming, and often take a lot of power. “Negligible” flux sites are also rarely studied because small fluxes are hard to resolve, measurements are time-consuming and costly, and it is hard to get funding to measure something when the error bars cross zero. However, such fluxes may not be negligible in time when multiplied by long time duration, for example, 340 out of 365 days per year. Similarly, these may not be negligible in space when multiplied by a large area. When GHG budgets are of interest, very small fluxes multiplied by hundreds of days or square kilometers, or both, could easily exceed large fluxes multiplied by few days or square kilometers. The new OF-CAES technology [1-7] has very low minimum detectable flux which may help make more of such measurements valuable and valid in both time and space. The presentation will demonstrate the field data on the N2O and CH4 soil flux performance of this new technology. Conceptual simulations will demonstrate the significant advantages of using the technology when measuring small N2O and CH4 fluxes over time and space. References: [1] Burba, 2021. Eddy Covariance Method for Scientific, Regulatory, and Commercial Applications. LI-COR Biosciences, 660 pp (under review) [2] Burba, 2021. Atmospheric Flux Measurements. In Advances in Spectroscopic Monitoring of the Atmosphere. Elsevier Science, 618 pp [3] Koulikov and Kachanov, 2014. Laser-based cavity-enhanced optical absorption gas analyzer with laser feedback optimization. US Patent 8659758 [4] Leggett et al, 2019. Development of Trace CH4 and CO2 Analyzers: Performance Evaluation Studies, GCWerks Integration, and Field Results. AGUFM [5] Minish et al, 2019. New High-Precision Low-Power CO2 and CH4 Analyzers for Multiple Applications. Geophysical Research Abstracts, Vol. 21 [6] Romanini et al, 2014. Introduction to cavity-enhanced absorption spectroscopy. In Cavity-Enhanced Spectroscopy and Sensing. Springer, 546 pp [7] Xu et al, 2020. How do soil temperature and moisture regulate N2O flux from an urban lawn? AGUFM