In order to constrain the greenhouse gas budget from an agriculture-dominated landscape, we conducted a tall tower measurement campaign in August and September, 2009 and, by doing so, developed a top-down estimate of carbon dioxide (CO2), CH4, and N2O fluxes. Our experiment made use of a 244m tall communication tower (44║41'19''N, 93║04'22''W) in Minnesota. The tower is located 20 km south of Minneapolis, and the footprint of the tower during the observation period was dominated by corn, soybean, and other agricultural crops. The CO2 concentrations were measured continuously using a Tunable Diode Laser (TDL) with air samples taken at four levels, 32 m, 56 m, 100 m and 200 m, while CH4 and N2O concentrations were measured using a second TDL with air samples taken at two levels, 3 m and 200 m. During the observation period, the vertical gradients indicated that the landscape was a source of N2O and CH4 and a sink of CO2. Comparing the CO2, CH4, and N2O concentrations at 200 m with the National Oceanic & Atmospheric Administration (NOAA) background site yields consistent results.
We used the tall tower observations and the equilibrium boundary layer concept with NCEP_Reanalysis 2 data (provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, at http://www.esrl.noaa.gov/psd/ ) to generate a preliminary estimate of the CO2, N2O, and CH4 budget. By type, the greenhouse gas fluxes during the observation period were: -1.4 Ámol m-2 s-1 for CO2, 12 nmol m-2 s-1 for CH4, and 0.36 nmol m-2 s-1 for N2O. To test the robustness of the equilibrium boundary layer concept, we compared the result with the CO2 flux measured by eddy covariance at the 100 m level of the tall tower and to a bottom-up estimate based on the CO2 flux measured from within the footprint of the tall tower. Our preliminary results suggest that the equilibrium boundary layer concept may lead to a large underestimation of the magnitude of the land surface flux.
Finally, our research will examine other top-down approaches including the Convective Boundary Layer Budget (CBL) Method and the Stochastic Time-Inverted Lagrangian Transport (STILT) modelŚin order to estimate greenhouse gas fluxes for the region and to evaluate the differences and uncertainties associated with these approaches.