Abstract. Recent advances in laser spectrometry offer new opportunities to investigate the soil–atmosphere exchange of nitrous oxide. During two field campaigns conducted at a grassland site and a willow field, we tested the performance of a quantum cascade laser (QCL) connected to a newly developed automated chamber system against a conventional gas chromatography (GC) approach using the same chambers plus an automated gas sampling unit with septum capped vials and subsequent laboratory GC analysis. Through its high precision and time resolution, data of the QCL system were used for quantifying the commonly observed nonlinearity in concentration changes during chamber deployment, making the calculation of exchange fluxes more accurate by the application of exponential models. As expected, the curvature values in the concentration increase was higher during long (60 min) chamber closure times and under high-flux conditions (FN2O > 150 µg N m−2 h−1) than those values that were found when chambers were closed for only 10 min and/or when fluxes were in a typical range of 2 to 50 µg N m−2 h−1. Extremely low standard errors of fluxes, i.e., from  ∼  0.2 to 1.7 % of the flux value, were observed regardless of linear or exponential flux calculation when using QCL data. Thus, we recommend reducing chamber closure times to a maximum of 10 min when a fast-response analyzer is available and this type of chamber system is used to keep soil disturbance low and conditions around the chamber plot as natural as possible. Further, applying linear regression to a 3 min data window with rejecting the first 2 min after closure and a sampling time of every 5 s proved to be sufficient for robust flux determination while ensuring that standard errors of N2O fluxes were still on a relatively low level. Despite low signal-to-noise ratios, GC was still found to be a useful method to determine the mean the soil–atmosphere exchange of N2O on longer timescales during specific campaigns. Intriguingly, the consistency between GC and QCL-based campaign averages was better under low than under high N2O efflux conditions, although single flux values were highly scattered during the low efflux campaign. Furthermore, the QCL technology provides a useful tool to accurately investigate the highly debated topic of diurnal courses of N2O fluxes and its controlling factors. Our new chamber design protects the measurement spot from unintended shading and minimizes disturbance of throughfall, thereby complying with high quality requirements of long-term observation studies and research infrastructures.

<p><strong>Abstract.</strong> Recent advances in laser spectrometry offer new opportunities to investigate soil-atmosphere exchange of nitrous oxide. During two field campaigns conducted at a grassland site and a willow field, we tested the performance of a quantum cascade laser (QCL) connected to a newly developed automated chamber system against a conventional gas chromatography (GC) approach using the same chambers plus an automated gas sampling unit with septum capped vials and subsequent laboratory GC analysis. Through its high precision and time resolution, data of the QCL system were used for quantifying the commonly observed non-linearity in concentration changes during chamber deployment, making the calculation of exchange fluxes more accurate by the application of exponential models. As expected, the curvature in the concentration increase was higher during long (60 min) chamber closure times and under high flux conditions (<i>F</i><sub>N2O</sub> > 150 µg N m<sup>−2</sup> h<sup>−1</sup>) than those that were found when chambers were closed for only 10 min and/or fluxes were in a typical range of 2 to 50 µg N m<sup>−2</sup> h<sup>−1</sup>. Extremely low standard errors of fluxes, i.e. ~0.1 % of the flux value, were observed regardless of linear or exponential flux calculation when using QCL data. Thus, we recommend reducing chamber closure times to a maximum of 10 min when high-frequency measurements are available to keep soil disturbance low and conditions around the chamber plot as natural as possible. If instrumentation with high-frequency resolution is available, sampling times from 1 to 5 s proved to be sufficient for robust flux determination assuring standard errors of N<sub>2</sub>O fluxes still being on a relatively low level. Despite low signal to noise ratios, GC was still found to be a useful method to determine soil-atmosphere exchange of N<sub>2</sub>O at longer time scales, i.e. seasons to years, e.g., when the main focus of the study is to investigate site budgets. Intriguingly, the consistency between GC and QCL-based campaign averages was better under low than under high N<sub>2</sub>O efflux conditions, although single flux values were highly scattered during the low efflux campaign. Furthermore, the QCL technology provides a useful tool to accurately investigate the highly debated topic of diurnal courses of N<sub>2</sub>O fluxes and its controlling factors. Our new chamber design reduces the disturbance of the soil and complies with high quality requirements of long-term observation studies and research infrastructures.</p>

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.

Introduction:We aimed to evaluate the performance of the fully automated multiparameter CN-6000 hemostasis analyzer.Methods: Performance evaluation of the CN-6000 analyzer was conducted for 10 tests including prothrombin time (PT), activated partial prothrombin time (aPTT), fibrinogen level, anti-Xa activity, and antithrombin activity using a unique portfolio of liquid ready-to-use reagents. Precision, sample and reagent carryovers, throughput, and sample turnaround time (STAT) function were prospectively assessed. Results from 343 samples (normal subjects, critically ill patients, patients receiving anticoagulants, subjects with high or low fibrinogen levels, and patients with decreased levels of factor II, V, VII, and X) were compared to those obtained on the STA-R Max 2® analyzer using dedicated reagents.Results: Total precision (coefficient of variation) was below 7% for all parameters in both normal and pathological ranges. For all analyzed parameters, results obtained on the CN-6000 were strongly correlated with those obtained on the STA-R Max 2®analyzer. Agreement between both instruments was excellent for all assays. The CN-6000 demonstrated a 30% higher throughput compared to the STA-R Max 2® (258 vs 185 tests per hour for a panel of tests including PT, aPTT, fibrinogen, factor V, anti-Xa, and D-Dimer). STAT turnaround time for critical care samples testing was <7 minutes. Conclusions:The CN-6000 analyzer performs equivalently or better than the STA-R Max 2® with a significantly improved throughput. This new hemostasis multiparameter analyzer appears to be particularly well suited for coagulation laboratories which require high sample throughput and manage high numbers of nonstandard and critical care samples.

&lt;p&gt;The increasing frequency and amplitude of extreme climatic events may decline ecosystem productivity and disturb the global carbon cycle. Recent and upcoming advances in remote sensing technology, such as hyperspectral reflectance and chlorophyll sun-induced fluorescence (SIF) missions, are boosting research on the monitoring of vegetation responses to heat and drought stress. To understand the impacts of stress on vegetation and the corresponding optical signals that can be sensed from space, it is essential to monitor the continuous dynamics of ecosystem carbon and water fluxes and optical signal responses to environmental changes on the ground.&lt;/p&gt;&lt;p&gt;We collected a unique dataset of synergistic observations of remote sensing and carbon-water flux measurements from multiple field sites of different vegetation types. This dataset elucidated variations of physiology, fluxes, and optical signals, including SIF and spectral vegetation indices. For example, in light-sensitive beech forests in Germany, we found that photoprotection is generally active. Gross primary productivity (GPP) and surface conductance (Gs) clearly decreased when heatwaves occurred. On the contrary, chlorophyll content changed only marginally, which was reflected by minimal changes in the chlorophyll index at red edge (CIred). The photochemical reflectance index (PRI), related to non-photochemical quenching (NPQ) via xanthophyll&amp;#180;s cycle, was sensitive to flash heat stress and related to vapor pressure deficit (VPD). But for longer and lower intensity of stress in another event, PRI only changed marginally. SIF was more sensitive to incident radiation (PPFD), but did not decrease with increasing air temperature (Ta) and VPD. However, SIF yield (the ratio of SIF and absorbed photosynthetically active radiation) decreased significantly during the heatwave. In contrast, in the light and heat-tolerant rice paddy in China, we observed that vegetation did not show negative effects at the early growing stage (nutritive growth) during an extreme heatwave (Ta&gt;35 &amp;#778;C). Due to the high relative humidity (from evaporated water), VPD remained low despite the high temperatures. GPP increased slightly accompanied by a small decrease of Gs as VPD slightly increased. SIF, SIF yield, and PRI noticeably increased with increasing CIred, indicating that heat might have accelerated the physiology rather than stressed plants in the rice paddy, which could be due to an overall higher temperature optimum compared to the European beach forest.&lt;/p&gt;&lt;p&gt;Our results demonstrate that water supply shortage combined with heat waves can cause immediate down-regulation of photosynthesis and that the new remote sensing missions could detect this vegetation response. However, if the water supply is abundant during the heatwave, responses of both physiological and remote sensing parameters may not be sensitive to heat stress. Due to species and ecosystem differences in terms of heat resistance, the global response of vegetation remains hard to predict indicating the need to remotely monitor these responses in order to improve process-based models. The outcomes of this work will possibly provide new insights on the utilization of novel optical remote sensing information for vegetation monitoring during extreme events.&lt;/p&gt;