光子学报, 2020, 49 (4): 0404002, 网络出版: 2020-04-24
工业SO2及碳黑颗粒紫外成像遥感监测技术
Remote Sensing and Monitoring of Industrial SO2 and Carbon Black Particles with Ultraviolet Imaging Technology
光学遥感 紫外成像 空气污染 吸收光谱 图像处理 Optical remote sensing UV imaging Air pollution Absorption spectra Image processing
摘要
为了准确有效监测工业烟囱排放,基于SO2及碳黑颗粒物的光学特性,设计并研制出一套双通道紫外成像遥感监测系统.该成像系统的两个光谱通道的中心波长分别定于310 nm和330 nm,利用两个通道的光学厚度之差反演SO2浓度图像,颗粒物浓度图像由330 nm通道获取,根据浓度图像结合光流法获取烟羽运动速度,进而计算得出SO2和碳黑颗粒物的排放速率.结果表明,该工业烟囱的SO2及碳黑颗粒物排放速率分别为72.48±3.16 kg/h和6.33±1.18 kg/h.实验采用紫外相机同时对工业烟囱排放的SO2及碳黑颗粒物进行监测,实验表明双通道紫外成像遥感监测兼具高时间分辨率与高空间分辨率,测量结果准确直观,在工业废气污染、船舶尾气污染以及火山喷发污染排放遥感监测中具有非常明显的技术优势及巨大的应用前景.
Abstract
In order to monitor industrial chimney emissions accurately and effectively, based on the optical properties of SO2 and carbon black particles, a dual-channel ultraviolet imaging remote sensing monitoring system was developed. The center wavelength of the two spectral channels were set at 310 nm and 330 nm, respectively. The SO2 concentration image was obtained by the optical thickness difference of the two channels, and the particles concentration image was obtained by the 330 nm channel. With the plume speed obtained from the density image by the Optical-flow method, the emission rates of SO2 and carbon black particle were calculated from them. The results show that the emission rates of SO2 and carbon black particles from the industrial chimney are 72.48±3.16 kg/h and 6.33±1.18 kg/h, respectively. In this experiment, the SO2 and carbon black particles emitted from industrial chimney were monitored by ultraviolet cameras simultaneously. A high time and spatial resolution was provided with dual-channel ultraviolet imaging remote sensing monitoring in this experiment, and the measurement results are accurate and intuitive. This method has obvious technical advantages and great application prospects in remote sensing of industrial exhaust, ship exhaust and volcanic eruption pollutions.
段为民, 熊远辉, 陈振威, 于光保, 刘林美, 李发泉, 武魁军. 工业SO2及碳黑颗粒紫外成像遥感监测技术[J]. 光子学报, 2020, 49(4): 0404002. Wei-min DUAN, Yuan-hui XIONG, Zhen-wei CHEN, Guang-bao YU, Lin-mei LIU, Fa-quan LI, Kui-jun WU. Remote Sensing and Monitoring of Industrial SO2 and Carbon Black Particles with Ultraviolet Imaging Technology[J]. ACTA PHOTONICA SINICA, 2020, 49(4): 0404002.