Computer vision for improved estimates of SO₂ emission rates and plume dynamics

Imaging cameras operating at ultraviolet (UV) and infrared (IR) wavelengths can measure sulphur dioxide (SO₂) gas path concentrations or slant column densities. These measurements are useful in a variety of applications including the monitoring of emissions from volcanoes and also emissions from stacks at industrial plants and on ships. The usefulness of these data is increased if the emission rates (or fluxes) of the gases can also be estimated. Here we present an optical flow algorithm that allows rapid and accurate estimates of emission rates using both UV and IR camera imagery sampling at around 1 Hz or higher. Examples are provided from measurements made at Turrialba volcano, Costa Rica, and also at a ship in Hong Kong harbour. Other aspects of the properties of the fluid flow are also introduced, notably the divergence and the vorticity of the two-dimensional wind field. We demonstrate how the divergence can be used in a new method to calculate the emission rate and show how rotational effects observed in volcanic plumes and the resulting entrainment of ambient air affects plume rise and can be observed using vorticity. This is an important aspect for understanding the emplacement of gases and particles into the atmosphere that are subsequently transported by atmospheric winds, sometimes causing pollution episodes at long distances from the source.

工作在紫外（ultraviolet, UV）与红外（infrared, IR）波段的成像相机，可用于测定二氧化硫（sulphur dioxide, SO₂）的气体路径浓度与斜柱密度。此类测量具备多领域应用价值，涵盖火山排放监测，以及工业厂房、船舶的烟囱排放监测。若可同时估算该气体的排放速率（或通量），则此类数据的实用价值将进一步提升。本文提出一种光流（optical flow）算法，可利用采样频率约1 Hz或更高的紫外、红外相机图像，快速且精准地估算气体排放速率。文中给出了哥斯达黎加图里亚尔瓦火山（Turrialba volcano）以及香港港的实测案例。此外还介绍了流体流动特性的其他方面，重点阐述了二维风场的散度（divergence）与涡度（vorticity）。我们演示了如何将散度应用于一种全新的排放速率计算方法，并阐明了火山羽流中观测到的旋转效应，以及由此引发的环境空气卷挟过程如何影响羽流抬升，且可通过涡度对该效应进行观测。这一方面对于理解气体与颗粒物进入大气后的扩散过程至关重要——这些物质随后会被大气风场输送，有时会在距排放源较远的区域引发污染事件。