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Thank you for your request.

You will receive an email shortly.

If you do not receive it within 24 hours or if you have any questions, please contact LI-COR at 1-402-467-3576.

This quote is for the basic eddy covariance system. To get a personalized quote, customize your system.


Proven Performance

LI-COR gas analyzers have a proven track record in ecosystem-level gas exchange systems, making them the gas analyzers of choice for eddy covariance flux measurements.

An age-old question:
Sensor Separation or Colocation?

A quintessential problem of measurements concerns the measuring apparatus itself: How can you be sure that the thing you are measuring is unaffected by the sensors that measure it?

This problem is readily observed in measurements of wind speed, where the bulk of a relatively small anemometer transducer can affect the wind being measured (1, 2, 3, 4, 5, 6). The issue becomes more pronounced when a much larger gas analyzer or other structure is positioned in or near the sample volume, (7, 8) because such a structure adds to the total bulk (Figure 1).

Object near the
anemometer

Airflow

Figure 1. An object that is too close to the sonic anemometer—whether it is a tree branch, a tower support, or a gas analyzer—can cause flow distortion and lead to measurement errors.

An ideal eddy covariance system will provide colocated measurements of wind speed and gas densities with no bulk that affects the turbulent air flow. This is not practical, however, because gas analyzers and anemometers have physical components that can disrupt the turbulent air flow. Disruptions to turbulent flow from large objects near the sample volume are difficult to detect, and virtually impossible to correct, without data from a second anemometer on the same tower (6, 7, 8, 9). To date, there are no published equations to correct this issue.

Research shows that a simple way to avoid these problems is to maintain a small separation between the sonic anemometer and the gas analyzer. Sensor separation leads to a small correction that is easily implemented and verified during data processing (10, 11, 12).

To facilitate the optimal analyzer position, we developed a mounting solution that positions the gas analyzer at an appropriate distance from the Gill WindMaster or WindMaster Pro sonic anemometers. This mounting apparatus makes it easy to determine separation distances and to orient the eddy covariance system toward the prevailing wind for an ideal omnidirectional setup.

Consistent Performance Across the Full Temperature Range

LI‑COR non-dispersive infrared (NDIR) gas analyzers provide accurate gas concentration measurements over a wide range of temperatures, without additional ad-hoc corrections. The open path LI‑7500x and enclosed path LI‑7200x analyzers are designed to be used in challenging outdoor environments, where they are subject to large temperature extremes. Key optical components are actively temperature regulated, and electronics are designed to be stable over a wide range of temperatures. Together, these design features provide a stable platform for measuring absorptance of infrared light by the gas of interest.

Light absorption is related to gas number density through a calibration function based on a spectroscopic scaling law that can be readily verified, (13, 14) and has been used in LI‑COR gas analyzers since the mid-1980’s. When gas concentration is expressed as a number density, this scaling law does not require temperature as an input, yet it still provides accurate gas density measurements over a wide range of temperatures. Unlike laser-based instruments, LI‑COR NDIR analyzers do not require instantaneous measurements of gas temperature to measure accurate CO2 or water vapor densities.

The typical performance of LI‑COR gas analyzers over a range of temperatures and CO2 densities is shown in Figure 2. Data such as these are collected for each gas analyzer as a part of routine factory calibration. The data fall on a single line, from which we derive a calibration function, allowing the instrument to give accurate CO2 density measurements over a wide range of temperatures.

Due to careful optical and electronic design, the performance of LI‑COR NDIR analyzers is consistent with theoretical expectations. No design is perfect, however. Inevitable small residual temperature dependencies exist, and corrections for them are included in the calibration function. These are well constrained and are provided with the instrument specifications. Full calibration details are also provided with every instrument.

Figure 2. CO2 calibration curves for an LI‑7500RS gas analyzer at 6 temperatures. The relationship between CO2 density and absorption is consistent across the full temperature range of -24 to 44 °C.

A Time and a Place for Everything…

…if the timekeeper is an atomic clock and the place is georeferenced.

Each LI‑COR eddy covariance system includes a GPS antenna so that your flux measurements are georeferenced. Each instrument clock is synchronized to the GPS system clock and adjusted for your time zone.

The time setting is applied to other instruments in your system using the Precision Timekeeping Protocol (PTP). This ensures that the clocks are synced both within and between sites, while making it easy to present the spatial and temporal context of your results.

Access Your Flux Station
from Anywhere

Because LI‑COR eddy covariance systems use secure Internet communication protocols, you can remotely review the performance of your gas analyzer, correct issues, and even update software without going to your site.

With a dedicated network connection over a cellular, satellite, or local area network, you can connect your eddy covariance system to the FluxSuite™ Data Management System and view fully processed results in real time, and receive notification of issues with the system.

LI‑COR eddy covariance systems provide USB data logging, automatic data processing, and the ability to publish raw and processed data to a server. These features are included with each analyzer at no additional charge.

Citations

  1. Wyngaard, J. C., 1981. The effects of probe-induced flow distortion on atmospheric turbulence measurements. Journal of Applied Meteorology, 20: 784-794.
  2. Wyngaard, J. C., 1988. Flow-distortion effects on scalar flux measurements in the surface layer: Implications for sensor design. In Hicks, B. B. (Eds) Topics in Micrometeorology. A Festschrift for Arch Dyer. Springer, Dordrecht.
  3. Frank, J. M., W. J. Massman, and B. E. Ewers, 2013. Underestimates of sensible heat flux due to vertical velocity measurement errors in non-orthogonal sonic anemometers. Agricultural and Forest Meteorology, 171-172: 72-81.
  4. Horst, T. W., S. R. Semmer, and G. Maclean, 2015. Correction of a non-orthogonal, three-component sonic anemometer for flow distortion by transducer shadowing. Boundary-Layer Meteorology, 155 (3): 371-395.
  5. Frank, J. M., W. J. Massman, E. Swiatek, H. A. Zimmerman, and B. E. Ewers, 2016. All sonic anemometers need to correct for transducer and structural shadowing in their velocity measurements. Journal of Atmospheric and Oceanic Technology, 33(1): 149-167.
  6. Huq, S., F. De Roo, T. Foken, M. Mauder, 2017. Evaluation of probe-induced flow distortion of Campbell CSAT3 sonic anemometers by numerical simulation. Boundary-Layer Meteorology, 165(1): 9-28.
  7. Horst, T. W., R. Vogt, and S. P. Oncley, 2016. Measurements of flow distortion within the IRGASON integrated sonic anemometer and CO2/H2O gas analyzer. Boundary-Layer Meteorology, 160(1): 1-15.
  8. Dyer, A. J., 1981. Flow distortion by supporting structures. Boundary-Layer Meteorology, 20(2): 243-251.
  9. Grare, L., L. Lenain, and W. K. Melville, 2016. The influence of wind direction on Campbell Scientific CSAT3 and Gill R3-50 sonic anemometer measurements. Journal of Atmospheric and Oceanic Technology, 33(11): 2477-2497.
  10. Moore, C. J., 1986. Frequency response corrections for eddy covariance systems. Boundary-Layer Meteorology, 37: 17-35.
  11. Horst, T. W., and D. H. Lenschow, 2009. Attenuation of scalar fluxes measured with spatially-displaced sensors. Boundary-Layer Meteorology, 130(2): 275-300.
  12. Mauder, M., and T. Foken, 2011. Documentation and Instruction Manual of the Eddy-Covariance Software Package TK3.
  13. 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.
  14. 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, WI.

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