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Abstract. Eleven instruments for the measurement of ambient concentrations of atmospheric ammonia gas (NH3), based on eight different measurement methods were inter-compared above an intensively managed agricultural field in late summer 2008 in Southern Scotland. To test the instruments over a wide range of concentrations, the field was fertilised with urea midway through the experiment, leading to an increase in the average concentration from 10 to 100 ppbv. The instruments deployed included three wet-chemistry systems, one with offline analysis (annular rotating batch denuder, RBD) and two with online-analysis (Annular Denuder sampling with online Analysis, AMANDA; AiRRmonia), two Quantum Cascade Laser Absorption Spectrometers (a large-cell dual system; DUAL-QCLAS, and a compact system; c-QCLAS), two photo-acoustic spectrometers (WaSul-Flux; Nitrolux-100), a Cavity Ring Down Spectrosmeter (CRDS), a Chemical Ionisation Mass Spectrometer (CIMS), an ion mobility spectrometer (IMS) and an Open-Path Fourier Transform Infra-Red (OP-FTIR) Spectrometer. The instruments were compared with each other and with the average concentration of all instruments. An overall good agreement of hourly average concentrations between the instruments (R2>0.84), was observed for NH3 concentrations at the field of up to 120 ppbv with the slopes against the average ranging from 0.67 (DUAL-QCLAS) to 1.13 (AiRRmonia) with intercepts of −0.74 ppbv (RBD) to +2.69 ppbv (CIMS). More variability was found for performance for lower concentrations (<10 ppbv). Here the main factors affecting measurement precision are (a) the inlet design, (b) the state of inlet filters (where applicable), and (c) the quality of gas-phase standards (where applicable). By reference to the fast (1 Hz) instruments deployed during the study, it was possible to characterize the response times of the slower instruments.

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Fluxes of methane (CH 4 ) and nitrous oxide (N 2 O) are commonly measured with closed static chambers. Here, we analyse several of the uncertainties inherent in these measurements, including the accuracy of calibration gases, repeatability of the concentration measurements, choice of model used to calculate the flux and lack of fit to the model, as well as inaccuracies in measurements of sampling time, temperature, pressure and chamber volume. In an analysis of almost 1000 flux measurements from six sites in the UK, the choice of model for calculating the flux and model lack-of-fit were the largest sources of uncertainty. The analysis provides confidence intervals based on the measurement errors, which are typically 20%. Our best estimate, using the best-fitting model, but substituting the linear model in the case of concave fits, gave a mean flux that is 25% greater than that calculated with the linear model. The best-fit non-linear model provided a better (convex) fit to the data than linear regression in 36% of the measurements. We demonstrate a method to balance the number of gas samples per chamber (n samples ) and the number of chambers, so as to minimize the total uncertainty in the estimate of the mean flux for a site with a fixed number of gas samples. The standard error generally decreased over the available range in n samples , suggesting that more samples per chamber (at the expense of proportionally fewer chambers) would improve estimates of the mean flux at these sites.

Abstract.Managed grasslands are known to be an important source of N 2 O with estimated global losses of 2.5 Tg N 2 O-N yr −1 . Chambers are to date the most widely used method to measure N 2 O fluxes, but also micrometeorological methods are successfully applied. In this paper we present a comparison of N 2 O fluxes measured by non-steady state chambers and eddy covariance (EC) (using an ultra-sonic anemometer coupled with a tunable diode laser) from an intensively grazed and fertilised grassland site in South East Scotland. The measurements were taken after fertilisation events in 2003, 2007 and 2008. In four out of six comparison periods, a short-lived increase of N 2 O emissions was observed after mineral N application, returning to background level within 2-6 days. Highest fluxes were measured by both methods in July 2007 with maximum values of 1438 ng N 2 O-N m −2 s −1 (EC) and 651 ng N 2 O-N m −2 s −1 (chamber method). Negative fluxes above the detection limit were observed in all comparison periods by EC, while with chambers, the recorded negative fluxes were always below detection limit. Median and average fluxes over each period were always positive. Over all 6 comparison periods, 69 % of N 2 O fluxes measured by EC at the time of chamber closure were within the range of the chamber measurements. N 2 O fluxes measured by EC during the time of chamber closure were not consistently smaller, neither larger, compared to those measured by chambers: this reflects the fact that the different techniques integrate fluxes over different spatial and temporal scales. Large fluxes measured by chambers may be representing local hotspots providing a small contribution to the flux measured by the EC method which integrates over a larger area. The spatial variability from Correspondence to: S. K. Jones (stephanie.jones@sac.ac.uk) chamber measurements was high, as shown by a coefficient of variation of up to 139 %. No diurnal pattern of N 2 O fluxes was observed, possibly due to the small diurnal variations of soil temperature. The calculation of cumulative fluxes using different integration methods showed EC data provide generally lower estimates of N 2 O emissions than chambers.