Mark Heuer

Measurement of trace gas fluxes over an unfertilized agricultural field using the flux-gradient technique.

Trace gas fluxes exhibit extensive spatial and temporal variability that is dependent on a number of factors, including meteorology, ambient concentration, and emission source size. Previous studies have found that agricultural fertilization contributes to higher fluxes of certain gases. The magnitude of trace gas fluxes over unfertilized crops is still uncertain. In the present study, deposition of ammonia (NH), nitric acid (HNO), and sulfur dioxide (SO) was measured over unfertilized soybean using the flux-gradient technique. The eddy diffusivity was estimated from eddy covariance measurements of temperature fluxes, resulting in K of 0.64 ± 0.30 m s. Flux means and standard deviations were -0.14 ± 0.13, -0.22 ± 0.19, and -0.38 ± 0.54 μg m s for NH, HNO, and SO, respectively. Low concentrations of NH and HNO increased the relative uncertainties in the deposition velocities estimated from measured fluxes. This contributed to dissimilarities between deposition velocities estimated from the resistance analogy and deposition velocities estimated from fluxes. However, wet canopy conditions during the study may have led to an underestimation of deposition by the resistance analogy because the resistance method does not accurately describe the enhanced deposition rates that occur after dew formation. Quantification of vegetation characteristics, such as leaf wetness and apoplast chemistry, would be beneficial in future studies to more accurately determine stomatal resistance and its influence on fluxes.

Ambient ammonia in terrestrial ecosystems: A comparative study in the Tennessee Valley, USA

Atmospheric ammonia has been shown to degrade regional air quality and affect environmental health. In-situ measurements of ammonia are needed to determine how ambient concentrations vary in different ecosystems and the extent to which emission sources contribute to those levels. The objective of this study was to measure and compare ammonia concentrations in two Tennessee Valley (USA) ecosystems: a forested rural area and a metropolitan site adjacent to a main transportation route. Integrated samples of atmospheric ammonia were collected with annular denuder systems for ~4 weeks during the summer of 2009 in both ecosystems. Ancillary measurements of meteorological variables, such as wind direction and precipitation, were also conducted to determine any relationships with ammonia concentration. Measurements in the two ecosystems revealed ammonia concentrations that were mostly representative of background levels. Arithmetic means were 1.57±0.68 μg m(-3) at the metropolitan site and 1.60±0.77 μg m(-3) in the forest. The geometric mean concentrations for both sites were ~1.46 μg m(-3). Wind direction, and to a lesser extent air temperature and precipitation, did influence measured concentrations. At the metropolitan site, ammonia concentrations were slightly higher in winds emanating from the direction of the interstate highway. Meteorological variables, such as wind direction, and physical factors, such as topography, can affect measurement of ambient ammonia concentrations, especially in ecosystems distant from strong emission sources. The 12-h integrated sampling method used in this study was unable to measure frequent changes in ambient ammonia concentrations and illustrates the need for measurements with higher temporal resolution, at least ~1-2h, in a variety of diverse ecosystems to determine the behavior of atmospheric ammonia and its environmental effects.

Estimating Random Uncertainty in Airborne Flux Measurements over Alaskan Tundra: Update on the Flux Fragment Method

AbstractAirborne turbulence measurement gives a spatial distribution of air–surface fluxes that networks of fixed surface sites typically cannot capture. Much work has improved the accuracy of such measurements and the estimation of the uncertainty peculiar to streams of turbulence data measured from the air. A particularly significant challenge and opportunity is to distinguish fluxes from different surface types, especially those occurring in patches smaller than the necessary averaging length. The flux fragment method (FFM), a conditional-sampling variant of eddy covariance in the space–time domain, was presented in 2008. It was shown capable of segregating the mean flux density (CO2, H2O, sensible heat) in maize from that in soybeans over the patchwork farmlands of Illinois. This was, however, an ideal surface for the method, and the random-error estimate used a relatively rudimentary bootstrap resampling. The present paper describes an upgraded random-error estimate that accounts for the serial corre...