Abstract. SO₂ cameras are becoming an established tool for measuring sulfur dioxide (SO₂) fluxes in volcanic plumes with good precision and high temporal resolution. The primary result of SO₂ camera measurements are time series of two-dimensional SO₂ column density distributions (i.e. SO₂ column density images). However, it is frequently overlooked that, in order to determine the correct SO₂ fluxes, not only the SO₂ column density, but also the distance between the camera and the volcanic plume, has to be precisely known. This is because cameras only measure angular extents of objects while flux measurements require knowledge of the spatial plume extent. The distance to the plume may vary within the image array (i.e. the field of view of the SO₂ camera) since the plume propagation direction (i.e. the wind direction) might not be parallel to the image plane of the SO₂ camera. If the wind direction and thus the camera–plume distance are not well known, this error propagates into the determined SO₂ fluxes and can cause errors exceeding 50 %. This is a source of error which is independent of the frequently quoted (approximate) compensation of apparently higher SO₂ column densities and apparently lower plume propagation velocities at non-perpendicular plume observation angles.

Here, we propose a new method to estimate the propagation direction of the volcanic plume directly from SO₂ camera image time series by analysing apparent flux gradients along the image plane. From the plume propagation direction and the known location of the SO₂ source (i.e. volcanic vent) and camera position, the camera–plume distance can be determined. Besides being able to determine the plume propagation direction and thus the wind direction in the plume region directly from SO₂ camera images, we additionally found that it is possible to detect changes of the propagation direction at a time resolution of the order of minutes. In addition to theoretical studies we applied our method to SO₂ flux measurements at Mt Etna and demonstrate that we obtain considerably more precise (up to a factor of 2 error reduction) SO₂ fluxes. We conclude that studies on SO₂ flux variability become more reliable by excluding the possible influences of propagation direction variations.