Reactive nitrogen fluxes over peatland and forest ecosystems using micrometeorological measurement techniques

Abstract

Abstract. Interactions of reactive nitrogen (Nr) compounds between the atmosphere and the earth's surface play a key role in atmospheric chemistry and in understanding nutrient cycling of terrestrial ecosystems. While continuous observations of inert greenhouse gases through micrometeorological flux measurements have become a common procedure, information about temporal dynamics and longer-term budgets of Nr compounds is still extremely limited. Within the framework of the research projects NITROSPHERE and FORESTFLUX, field campaigns were carried out to investigate the biosphere–atmosphere exchange of selected Nr compounds over different land surfaces. The aim of the campaigns was to test and establish novel measurement techniques in eddy-covariance setups for continuous determination of surface fluxes of ammonia (NH3) and total reactive nitrogen (ΣNr) using two different analytical devices. While high-frequency measurements of NH3 were conducted with a quantum cascade laser (QCL) absorption spectrometer, a custom-built converter called Total Reactive Atmospheric Nitrogen Converter (TRANC) connected and operated upstream of a chemiluminescence detector (CLD) was used for the measurement of ΣNr. As high-resolution data of Nr surface–atmosphere exchange are still scarce but highly desired for testing and validating local inferential and larger-scale models, we provide access to campaign data including concentrations, fluxes, and ancillary measurements of meteorological parameters. Campaigns (n=4) were carried out in natural (forest) and semi-natural (peatland) ecosystem types. The published datasets stress the importance of recent advancements in laser spectrometry and help improve our understanding of the temporal variability of surface–atmosphere exchange in different ecosystems, thereby providing validation opportunities for inferential models simulating the exchange of reactive nitrogen. The dataset has been placed in the Zenodo repository (https://doi.org/10.5281/zenodo.4513854; Brümmer et al., 2022) and contains individual data files for each campaign.