We operated a vertically scanning lidar at the Los Angeles International Airport. The 355-nm wavelength pulses were eyesafe and invisible. The lidar was located about 400 m from the runway centerline and aimed across the runway where most of the aircraft held while waiting for takeoff clearance. By scanning up and down, we were able to map the intensity of scattering throughout a cross section of the jet engine plume every 5 seconds or so. The resulting data were analyzed to reveal the position and size of the plume after the engines ramped up and takeoff roll commenced. The results (Wayson et al. 2003) show that plume rise and vertical dispersion are significant, suggesting less severe air quality impact than if one just assumed a passive point source at engine height. One surprising result was that the “final” rise and dispersion of plumes from small commuter jet aircraft were on average quite similar to that of plumes from heavy, multi-engine aircraft. We intend to continue research on plume geometry to better understand factors like the dependence on engine setting (e.g., taxi versus takeoff power), atmospheric stability, engine size and type, and engine location on the airframe.
Brief, simple scattering calculations based on rough estimates of particles emitted by the aircraft were performed before the Los Angeles experiment to convince ourselves of the project’s feasibility. Our expectations were that: 1) scattering from particles emitted by the aircraft would often be sufficient to detect the plume; 2) for cleaner engines and hazier ambient conditions the aircraft plume might be hard or impossible to detect; and 3) the possibility exists for “negative” plumes, i.e., particles in hazy air passing through the engine might be volatized, reducing the lidar backscatter from the plume such that it would be less than backscatter from the ambient air. Indeed, we observed instances of all three, the third case being more common in humid conditions.
Success in the geometry measurements led us to consider measurement of the emission rate of soot. Because in situ measurements are so difficult, and are almost impossible for large numbers of aircraft during normal operations, a remote sensing capability would be of great benefit. The approach is to infer the flux of mass through the lidar scan plane and assume that it is equal to the emission rate. The main issues to be addressed in this method are: 1) Calibration of the lidar backscatter. Procedures are well established and relatively accurate. 2) Conversion factor between lidar backscatter and mass concentration. This depends on the particles’ index of refraction (relatively well known), particle size distribution (some information is available, but this will probably the biggest source of uncertainty in the method, at least initially), and particle shape (could be a source of significant uncertainty). 3) Contribution of ambient haze. How much is volatized by the engine, and how much is mixed into the plume as it disperses, must both be considered. We believe that simple theories and lidar data examined over many cases will allow us to sort this out with adequate accuracy. 4) Forward speed of the aircraft. The aircraft’s motion proportionately dilutes the concentrations. Quite accurate data on aircraft speed can be obtained based on video camera data or on typical performance profiles for each aircraft type. 5) Speed of the air in the plume normal to the lidar’s scan plane. This also proportionately dilutes the concentrations. Ambient wind measurements can be used if the plume is measured far enough behind the aircraft. Closer to the engine, air speeds must be measured, or models based on measurements applied.
The paper will discuss this approach in more detail, and estimate the uncertainty for inferred soot emission rates. One factor in favor of the lidar method is that emission rates are only poorly known now, so even a factor-of-two accuracy from the lidar would be highly valuable.
Wayson, R.L., G. G. Fleming, W. L. Eberhard, B. Kim, W. A. Brewer, J. Draper, J. Pehrson, and R. Johnson, 2003: The use of LIDAR to characterize aircraft exhaust plumes, Proceedings, 96th Ann. Meeting of AWMA, San Diego, CA, Air and Waste Management Association.