Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days

Abstract

Abstract:We performed measurements of SO 2 emissions with a high UV sensitive dual-camera optical system. Generally, in order to retrieve the two-dimensional SO 2 emission rates of a source, e.g., the slant column density of a plume emitted by a stack, one needs to acquire four images with UV cameras: two images including the emitting stack at wavelengths with high and negligible absorption features (λ on/off ), and two additional images of the background intensity behind the plume, at the same wavelengths as before. However, the true background intensity behind a plume is impossible to obtain from a remote measurement site at rest, and thus, one needs to find a way to approximate the background intensity. Some authors have presented methods to estimate the background behind the plume from two emission images. However, those works are restricted to dealing with clear sky, or almost homogeneously illuminated days. The purpose of this work is to present a new approach using background images constructed from emission images by an automatic plume segmentation and interpolation procedure, in order to estimate the light intensity behind the plume. We compare the performance of the proposed approach with the four images method, which uses, as background, sky images acquired at a different viewing direction. The first step of the proposed approach involves the segmentation of the SO 2 plume from the background. In clear sky days, we found similar results from both methods. However, when the illumination of the sky is non homogeneous, e.g., due to lateral sun illumination or clouds, there are appreciable differences between the results obtained by both methods. We present results obtained in a series of measurements of SO 2 emissions performed on a cloudy day from a stack of an oil refinery in Montevideo City, Uruguay. The results obtained with the UV cameras were compared with scanning DOAS measurements, yielding a good agreement.

Real-Time Monitoring of SO2 Emissions Using a UV Camera with Built-in NO2 and Aerosol Corrections

“…Figure 4 a,b shows a pair of the raw images ( and ) of an industrial plume. The raw images were processed following the protocols, which are already described in the literature [ 20 ], including the subtraction of a dark current and image matching. Simultaneously, the background sky images ( and ) of the plume can be constructed from the raw plume images by plume segmentation and interpolation.…”

“…Christoph Kern et al used seven different UV cameras and four different filters to continuously monitor the volcanic plumes in real-time [ 19 ]. Osorio, M et al proposed a new two-image method (2-IM) to acquire background images and quantify SO 2 emissions from industrial sources [ 20 ]. However, UV cameras are mostly used to measure higher concentrations of SO 2 emissions from volcanic sources.…”

Monitoring Sulfur Content in Marine Fuel Oil Using Ultraviolet Imaging Technology

“…Imaging detection technology inverts SO 2 concentration with 2D imaging information in images, and multiple tail plume images can be collected every second. As a result, imaging detection technology can retain the temporal and spatial variation characteristics successfully [19].…”

Measurement of three dimensional volcanic plume properties using multiple ground based infrared cameras

“…Almost all techniques used today integrate, out of necessity, over line-of-sight. These include both scanning Differential Optical Absorption Spectroscopy (DOAS) [23] and imaging techniques [24], [14]. This has two important ramifications if concentrations, rather than emission are to be retrieved: (1) an estimate of the third dimension is required, which often introduces significant error and (2) only an average concentration along the line of sight can be derived.…”