Surface–atmosphere exchange of ammonia over peatland using QCL-based eddy-covariance measurements and inferential modeling

Abstract

Abstract. Recent advances in laser spectrometry offer new opportunities to investigate ecosystem–atmosphere exchange of environmentally relevant trace gases. In this study, we demonstrate the applicability of a quantum cascade laser (QCL) absorption spectrometer to continuously measure ammonia concentrations at high time resolution and thus to quantify the net exchange between a seminatural peatland ecosystem and the atmosphere based on the eddy-covariance approach. Changing diurnal patterns of both ammonia concentration and fluxes were found during different periods of the campaign. We observed a clear tipping point in early spring with decreasing ammonia deposition velocities and increasingly bidirectional fluxes that occurred after the switch from dormant vegetation to CO2 uptake but was triggered by a significant weather change. While several biophysical parameters such as temperature, radiation, and surface wetness were identified to partially regulate ammonia exchange at the site, the seasonal concentration pattern was clearly dominated by agricultural practices in the surrounding area. Comparing the results of a compensation point model with our measurement-based flux estimates showed considerable differences in some periods of the campaign due to overestimation of non-stomatal resistances caused by low acid ratios. The total cumulative campaign exchange of ammonia after 9 weeks, however, differed only in a 6 % deviation with 911 and 857 g NH3-N ha−1 deposition being found by measurements and modeling, respectively. Extrapolating our findings to an entire year, ammonia deposition was lower than reported by Hurkuck et al. (2014) for the same site in previous years using denuder systems. This was likely due to a better representation of the emission component in the net signal of eddy-covariance fluxes as well as better adapted site-specific parameters in the model. Our study not only stresses the importance of high-quality measurements for studying and assessing land surface–atmosphere interactions but also demonstrates the potential of QCL spectrometers for continuous observation of reactive nitrogen species as important additional instruments within long-term monitoring research infrastructures such as ICOS or NEON at sites with strong nearby ammonia sources leading to relatively high mean background concentrations and fluxes.

NH<sub>3</sub> emissions from large point sources derived from CrIS and IASI satellite observations

“…The IASI-NNv2.2 product uses a neural network to link the hyper-spectral range index (HRI) with a set of parameters, representing the atmospheric state, to derive the total columns NH 3 . The near-real time IASI-NN data products have small discontinuities in the dataset following 25 updates on the meteorological parameters provided by EUMETSAT. The IASI-NNv2.2 product improved this by providing a reanalysis dataset (ANNI-NH 3 -v2.2R-I, here called IASI-NNv2.2(R)) that allows us here to evaluate the emissions estimates from year-to-year.…”

“…Finally, any locations from the set reported by Van Damme et al (2018) that were missing from our set have been appended to the final location list. 25 For a complete list of final locations see the supplementary material. The method used in this study requires a point source like emission source.…”

“…3 (c) and (d). As the background parameter is a single value the reconstruction will be missing some of the smaller concentration peaks surrounding the source 25 location seen in the top left and right plots.…”

“…Taking the standard deviation of the estimated emissions for each location and dividing it over the mean we find a calculated uncertainty of 2.6% for IASI and 3.1% for CrIS. 25…”

“…Therefore, in this study we used only observations during warmer conditions between the 1st of April and the 30th of September in order to optimize conditions to which the satellites are more sensitive for the Northern Hemisphere. Similarly, only observations made between the 1st of October and the 31st of March are used for the 25 Southern hemisphere. Besides the individual satellite product quality filters, we also correct for the influence of local events with anomalous concentrations, such as manure spreading and fire emissions, by applying a combination of two standard deviation filters.…”