Abstract. Remote sensing of the gaseous composition of non-eruptive, passively degassing volcanic plumes can be a tool to gain insight into volcano interior processes. Here, we report on a field study in September 2015 that demonstrates the feasibility of remotely measuring the volcanic enhancements of carbon dioxide (CO 2 ), hydrogen fluoride (HF), hydrogen chloride (HCl), sulfur dioxide (SO 2 ), and bromine monoxide (BrO) in the downwind plume of Mt. Etna using portable and rugged spectroscopic instrumentation. To this end, we operated the Fourier transform spectrometer EM27/SUN for the shortwave-infrared (SWIR) spectral range together with a co-mounted UV spectrometer on a mobile platform in direct-sun view at 5 to 10 km distance from the summit craters. The 3 days reported here cover several plume traverses and a sunrise measurement. For all days, intra-plume HF, HCl, SO 2 , and BrO vertical column densities (VCDs) were reliably measured exceeding 5 ×1016 , 2 ×10 17 , 5 ×10 17 , and 1 ×10 14 molec cm −2 , with an estimated precision of 2.2 ×10 15 , 1.3 ×10 16 , 3.6 ×10 16 , and 1.3 ×10 13 molec cm −2 , respectively. Given that CO 2 , unlike the other measured gases, has a large and wellmixed atmospheric background, derivation of volcanic CO 2 VCD enhancements ( CO 2 ) required compensating for changes in altitude of the observing platform and for background concentration variability. The first challenge was met by simultaneously measuring the overhead oxygen (O 2 ) columns and assuming covariation of O 2 and CO 2 with altitude. The atmospheric CO 2 background was found by identifying background soundings via the coemitted volcanic gases. The inferred CO 2 occasionally exceeded 2 × 10 19 molec cm −2 with an estimated precision of 3.7 × 10 18 molec cm −2 given typical atmospheric background VCDs of 7 to 8 × 10 21 molec cm −2 . While the correlations of CO 2 with the other measured volcanic gases confirm the detection of volcanic CO 2 enhancements, correlations were found of variable significance (R 2 ranging between 0.88 and 0.00). The intra-plume VCD ratios CO 2 / SO 2 , SO 2 / HF, SO 2 / HCl, and SO 2 / BrO were in the range 7.1 to 35.4, 5.02 to 21.2, 1.54 to 3.43, and 2.9 × 10 3 to 12.5 × 10 3 , respectively, showing pronounced day-to-day and intra-day variability.

Large-eddy simulation (LES) experiments have been performed using the Parallelized LES Model (PALM). A methodology for validating and understanding LES results for plume dispersion and concentration fluctuations in an atmospheric-like flow is presented. A wide range of grid resolutions is shown to be necessary for investigating the convergence of statistical characteristics of velocity and scalar fields. For the scalar, the statistical moments up to the fourth order and the shape of the concentration probability density function (p.d.f.) are examined. The mean concentration is influenced by grid resolution, with the highest resolution simulation showing a lower mean concentration, linked to larger turbulent structures. However, a clear tendency to convergence of the concentration variance is observed at the two higher resolutions. This behaviour is explained by showing that the mechanisms driving the mean and the variance are differently influenced by the grid resolution. The analysis of skewness and kurtosis allows also the obtaining of general results on plume concentration fluctuations. Irrespective of grid resolution, a family of Gamma p.d.f.s well represents the shape of the concentration p.d.f. but only beyond the peak of the concentration fluctuation intensity. In the early plume dispersion phases, the moments of the p.d.f. are in good agreement with those generated by a fluctuating plume model. To the best of our knowledge, our study demonstrates for the first time that, if resolution and averaging time are adequate, atmospheric LES provides a trustworthy representation of the high order moments of the concentration field, up to the fourth order, for a dispersing plume.

Ultraviolet (UV) SO 2 cameras have become a common tool to measure and monitor SO 2 emission rates, mostly from volcanoes but also from anthropogenic sources (e.g., power plants or ships). Over the past decade, the analysis of UV SO 2 camera data has seen many improvements. As a result, for many of the required analysis steps, several alternatives exist today (e.g., cell vs. DOAS based camera calibration; optical flow vs. cross-correlation based gas-velocity retrieval). This inspired the development of Pyplis (Python plume imaging software), an open-source software toolbox written in Python 2.7, which unifies the most prevalent methods from literature within a single, cross-platform analysis framework. Pyplis comprises a vast collection of algorithms relevant for the analysis of UV SO 2 camera data. These include several routines to retrieve plume background radiances as well as routines for cell and DOAS based camera calibration. The latter includes two independent methods to identify the DOAS field-of-view (FOV) within the camera images (based on (1) Pearson correlation and (2) IFR inversion method). Plume velocities can be retrieved using an optical flow algorithm as well as signal cross-correlation. Furthermore, Pyplis includes a routine to perform a first order correction of the signal dilution effect (also referred to as light dilution). All required geometrical calculations are performed within a 3D model environment allowing for distance retrievals to plume and local terrain features on a pixel basis. SO 2 emission rates can be retrieved simultaneously for an arbitrary number of plume intersections. Hence, Pyplis provides a state-of-the-art framework for more efficient and flexible analyses of UV SO 2 camera data and, therefore, marks an important step forward towards more transparency, reliability and inter-comparability of the results. Pyplis has been extensively and successfully tested using data from several field campaigns. Here, the main features are introduced using a dataset obtained at Mt. Etna, Italy on 16 September 2015.