Schröter Marc, Obermeier Andreas, Brüggemann Dieter, Plechschmidt Michael, Klemm Otto
Chair of Technical Thermodynamics and Transport Processes, Bayreuth Institute for Terrestrial Ecosystem Research, University of Bayreuth, Bayreuth, Germany.
J Air Waste Manag Assoc. 2003 Jun;53(6):716-23. doi: 10.1080/10473289.2003.10466213.
This paper describes remote monitoring of air pollutant emissions by a mobile lidar (light detection and ranging)/ sodar (sound detection and ranging) system. First, measurements are carried out in the flue gas plume of a public power plant. The investigations focus mainly on quantifying SO2 emissions, but the uncertainties of such measurements are also emphasized. Furthermore, an example providing valuable data sets for the development and validation of plume dispersion models is outlined with measurements of the dilution of SO2 along the plume axis. Series of repeated determinations of SO2 emissions show a large variation in the obtained flux values, with moderate margins of error. Incomplete recording of the plume within the individual lidar scans, induced by strong looping movements of the flue gas plume, predominantly causes the variations of flux values. Therefore, the highest flux values determined are considered to be the most exact. This is verified by a comparison of measured fluxes with in situ measurements made by the plant operators. The results further indicate that lidar measurements illustrate the location and dimension of aerosol plumes better than the location and dimension of the plumes of gaseous compounds. The wind direction affecting the plume at any moment can be determined faster by lidar than by sodar because the latter requires much longer time intervals of signal averaging. Measurements show higher concentrations of SO2 compared with results from a Gaussian plume model for periods of less than 5 min after dispersion. The findings emphasize the suitability of remote sensing for detecting emissions and for investigating the propagation and dilution of air pollutant plumes.
本文介绍了利用移动激光雷达(光探测与测距)/声雷达(声探测与测距)系统对空气污染物排放进行远程监测的情况。首先,在一家公共发电厂的烟道气羽流中进行了测量。研究主要集中在量化二氧化硫排放,但也强调了此类测量的不确定性。此外,通过沿羽流轴对二氧化硫稀释情况的测量,概述了一个为羽流扩散模型的开发和验证提供有价值数据集的示例。对二氧化硫排放的一系列重复测定显示,所获得的通量值变化很大,误差幅度适中。烟道气羽流的强烈回旋运动导致在单个激光雷达扫描中羽流记录不完整,这主要造成了通量值的变化。因此,所确定的最高通量值被认为是最准确的。通过将测量通量与电厂操作人员进行的现场测量结果进行比较,这一点得到了验证。结果还表明,激光雷达测量在显示气溶胶羽流的位置和尺寸方面比气态化合物羽流的位置和尺寸更好。激光雷达比声雷达能更快地确定任何时刻影响羽流的风向,因为声雷达需要更长的信号平均时间间隔。测量结果显示,在扩散后不到5分钟的时间段内,与高斯羽流模型的结果相比,二氧化硫浓度更高。这些发现强调了遥感技术在检测排放以及研究空气污染物羽流的传播和稀释方面的适用性。