High temporal frequency measurements of greenhouse gas emissions from soils
- 1The Woods Hole Research Center, 149 Woods Hole Rd, Falmouth, MA 02540, USA
- 2Landcare Research, Riddett Road, Massey University, Palmerston North, 4472, New Zealand
Abstract. Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) are the most important anthropogenic greenhouse gases (GHGs). Variation in soil moisture can be very dynamic, and it is one of the dominant factors controlling the net exchange of these three GHGs. Although technologies for high-frequency, precise measurements of CO2 have been available for years, methods for measuring soil fluxes of CH4 and N2O at high temporal frequency have been hampered by lack of appropriate technology for in situ real-time measurements. A previously developed automated chamber system for measuring CO2 flux from soils was configured to run in line with a new quantum cascade laser (QCLAS) instrument that measures N2O and CH4. Here we present data from a forested wetland in Maine and an agricultural field in North Dakota, which provided examples of both net uptake and production for N2O and CH4. The objective was to provide a range of conditions in which to run the new system and to compare results to a traditional manual static-chamber method.
The high-precision and more-than-10-times-lower minimum detectable flux of the QCLAS system, compared to the manual system, provided confidence in measurements of small N2O uptake in the forested wetland. At the agricultural field, the greatest difference between the automated and manual sampling systems came from the effect of the relatively infrequent manual sampling of the high spatial variation, or "hot spots", in GHG fluxes. Hot spots greatly influenced the seasonal estimates, particularly for N2O, over one 74-day alfalfa crop cycle. The high temporal frequency of the automated system clearly characterized the transient response of all three GHGs to precipitation and demonstrated a clear diel pattern related to temperature for GHGs. A combination of high-frequency automated and spatially distributed chambers would be ideal for characterizing hot spots and "hot moments" of GHG fluxes.