Automated, low-power chamber system for measuring nitrous oxide emissions.

Continuous measurement of soil NO emissions is needed to constrain NO budget and emission factors. Here, we describe the performance of a low-power Teledyne NO analyzer and automated chamber system, powered by wind and solar, that can continuously measure soil NO emissions. Laboratory testing of the analyzer revealed significant temperature sensitivity, causing zero drift of -10.6 nmol mol °C. However, temperature-induced span drift was negligible, so the associated error in flux measurement for a typical chamber sampling period was on the order of 0.016 nmol m s. The 1-Hz precision of the analyzer over a 10-min averaging interval, after wavelet decomposition, was 1.5 nmol mol, equal to that of a tunable diode laser NO analyzer. The solar/wind hybrid power system performed well during summer, but system failures increased in frequency in spring and fall, usually at night. Although increased battery storage capacity would decrease down time, supplemental power from additional sources may be needed to continuously run the system during spring and fall. The hourly flux data were numerically subsampled at weekly intervals to assess the accuracy of integrated estimates derived from manually sampling static chambers. Weekly sampling was simulated for each of the five weekdays and for various times during each day. For each weekday, the cumulative N emissions estimate using only morning measurements was similar (within 15%) to the estimate using only afternoon measurements. Often, weekly sampling partially or completely missed large episodic NO emissions that continuous automated chamber measurements captured, causing weekly measurements to underestimate cumulative N emissions for 9 of the 10 sampling scenarios.

Identification and correction of spectral contamination in 2H/1H and 18O/16O measured in leaf, stem, and soil water.

Plant water extracts typically contain organic materials that may cause spectral interference when using isotope ratio infrared spectroscopy (IRIS), resulting in errors in the measured isotope ratios. Manufacturers of IRIS instruments have developed post-processing software to identify the degree of contamination in water samples, and potentially correct the isotope ratios of water with known contaminants. Here, the correction method proposed by an IRIS manufacturer, Los Gatos Research, Inc., was employed and the results were compared with those obtained from isotope ratio mass spectrometry (IRMS). Deionized water was spiked with methanol and ethanol to create correction curves for δ(18)O and δ(2)H. The contamination effects of different sample types (leaf, stem, soil) and different species from agricultural fields, grasslands, and forests were compared. The average corrections in leaf samples ranged from 0.35 to 15.73‰ for δ(2)H and 0.28 to 9.27‰ for δ(18)O. The average corrections in stem samples ranged from 1.17 to 13.70‰ for δ(2)H and 0.47 to 7.97‰ for δ(18)O. There was no contamination observed in soil water. Cleaning plant samples with activated charcoal had minimal effects on the degree of spectral contamination, reducing the corrections, by on average, 0.44‰ for δ(2)H and 0.25‰ for δ(18)O. The correction method eliminated the discrepancies between IRMS and IRIS for δ(18)O, and greatly reduced the discrepancies for δ(2)H. The mean differences in isotope ratios between IRMS and the corrected IRIS method were 0.18‰ for δ(18)O, and -3.39‰ for δ(2)H. The inability to create an ethanol correction curve for δ(2)H probably caused the larger discrepancies. We conclude that ethanol and methanol are the primary compounds causing interference in IRIS analyzers, and that each individual analyzer will probably require customized correction curves.