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Automated, Low-Power Chamber System for Measuring Nitrous Oxide Emissions

Joel J. Fassbinder, Natalie M. Schultz, John M. Baker, Timothy J. Griffis
Journal of environmental quality 2013 v.42 no.2 pp. 606-614
measuring devices, autumn, laboratory techniques, greenhouse gas emissions, lasers, solar energy, automation, soil, spring, equipment performance, rain, summer, temperature, wind power, nitrous oxide
Continuous measurement of soil N₂O emissions is needed to constrain N₂O budget and emission factors. Here, we describe the performance of a low-power Teledyne N₂O analyzer and automated chamber system, powered by wind and solar, that can continuously measure soil N₂O emissions. Laboratory testing of the analyzer revealed significant temperature sensitivity, causing zero drift of −10.6 nmol mol⁻¹ °C⁻¹. 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⁻² s⁻². The 1-Hz precision of the analyzer over a 10-min averaging interval, after wavelet decomposition, was 1.5 nmol mol⁻¹, equal to that of a tunable diode laser N₂O 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 N₂O emissions that continuous automated chamber measurements captured, causing weekly measurements to underestimate cumulative N emissions for 9 of the 10 sampling scenarios.