From tropics to tundra, the LI-7200RS performs well in the most extreme environments.

Stability and Drift Resistance

The accumulation of dust, pollen, chemical residues, and other contaminants on the optics of an unfiltered enclosed gas analyzer can lead to measurement drift and cause gaps in datasets. This is not a significant problem if an instrument is filtered and regularly maintained. If an instrument is unfiltered or not maintained, however, there is risk that contaminants will affect measurements.

Innovations to the optics and electronics ensure that the LI-7200RS collects more accurate and dependable data—even as contaminants begin to accumulate on the optics.

Data from 13 instruments at 5 sites—with exposure to different levels of contamination—consistently show that the LI-7200RS provides more stable water vapor measurements than the original LI-7200 (Figure 1). CO2 measurements (not shown) are similar to or slightly better than those of the LI-7200.

Figure 1. Water vapor measurements from two unfiltered LI-7200RS instruments and two unfiltered LI-7200 analyzers (average and spread). The y-axis shows deviation from a control reference. Measurements from the LI-7200RS analyzers drifted several times less and have smaller instrument-to-instrument variability than those from the original LI-7200.

High Speed Temperature and Pressure Measurements

High-speed temperature and pressure measurements of sampled air—the actual air in the gas analyzer cell—provide the data required to compute fast dry mole fraction, and thus compute accurate fluxes. The LI-7200RS measures air temperature and pressure with a sophisticated system of thermocouples and pressure sensors. This patented configuration ensures true alignment of temperature, pressure, and gas densities, to ensure the most accurate flux results.

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Figure 2. The LI-7200RS measures the sample air temperature and pressure with every gas density measurement. Dampened, low-speed temperature measurements of block temperature will not provide the data required to compute fast mole fractions.

Although the absence of fast air temperature and pressure measurements may appear negligible on half-hourly fluxes, the problems become apparent when computing carbon budgets (Figure 3), which can accrue large differences.

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Figure 3. Errors from slow, dampened temperature and pressure measurements, rather than fast measurements of sampled air, accumulate quickly, and become significant after a few days of data collection at this site. By day 10, fluxes were underestimated by 2.4 times.
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