Lidar Observations of Aircraft Exhaust PlumesSource: Journal of Atmospheric and Oceanic Technology:;2010:;volume( 027 ):;issue: 010::page 1638DOI: 10.1175/2010JTECHA1412.1Publisher: American Meteorological Society
Abstract: A series of field campaigns has been made at British airports using a rapid-scanning lidar and other instrumentation in order to measure the dispersion of exhaust plumes from commercial aircraft. The lidar operated at a wavelength of 355 nm and was thus effectively eye safe. Analysis software for the lidar signals has been elaborated to enable the rather weak signals (typically a few tens of percent of ambient backscatter) from aircraft exhaust to be distinguished and to facilitate automatic processing of the measurements obtained. Such processing can deliver images, animations, and numerical parameterizations of the dispersing plumes. Overall, 1353 air traffic movements were monitored over two campaigns at Manchester and 439 in a single campaign at Heathrow. All modes were observed: taxiing, takeoff, rotation, climb-out, approach, and landing. Of these, the most complete dataset was that obtained for the start of the takeoff run: in this mode, the source is on full power but is still moving relatively slowly. Emissions thus remain at their most concentrated. For the same reason, this is the most important mode in respect to local air quality. Tire smoke on landing was likewise easily detected. Conversely, the lidar could only see the engine emissions from about 30% of the aircraft on approach. These data have been archived in an accessible form and are currently being used to develop improved regulatory dispersion models for airports.
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| contributor author | Bennett, Michael | |
| contributor author | Christie, Simon | |
| contributor author | Graham, Angus | |
| contributor author | Raper, David | |
| date accessioned | 2017-06-09T16:37:16Z | |
| date available | 2017-06-09T16:37:16Z | |
| date copyright | 2010/10/01 | |
| date issued | 2010 | |
| identifier issn | 0739-0572 | |
| identifier other | ams-71081.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4212933 | |
| description abstract | A series of field campaigns has been made at British airports using a rapid-scanning lidar and other instrumentation in order to measure the dispersion of exhaust plumes from commercial aircraft. The lidar operated at a wavelength of 355 nm and was thus effectively eye safe. Analysis software for the lidar signals has been elaborated to enable the rather weak signals (typically a few tens of percent of ambient backscatter) from aircraft exhaust to be distinguished and to facilitate automatic processing of the measurements obtained. Such processing can deliver images, animations, and numerical parameterizations of the dispersing plumes. Overall, 1353 air traffic movements were monitored over two campaigns at Manchester and 439 in a single campaign at Heathrow. All modes were observed: taxiing, takeoff, rotation, climb-out, approach, and landing. Of these, the most complete dataset was that obtained for the start of the takeoff run: in this mode, the source is on full power but is still moving relatively slowly. Emissions thus remain at their most concentrated. For the same reason, this is the most important mode in respect to local air quality. Tire smoke on landing was likewise easily detected. Conversely, the lidar could only see the engine emissions from about 30% of the aircraft on approach. These data have been archived in an accessible form and are currently being used to develop improved regulatory dispersion models for airports. | |
| publisher | American Meteorological Society | |
| title | Lidar Observations of Aircraft Exhaust Plumes | |
| type | Journal Paper | |
| journal volume | 27 | |
| journal issue | 10 | |
| journal title | Journal of Atmospheric and Oceanic Technology | |
| identifier doi | 10.1175/2010JTECHA1412.1 | |
| journal fristpage | 1638 | |
| journal lastpage | 1651 | |
| tree | Journal of Atmospheric and Oceanic Technology:;2010:;volume( 027 ):;issue: 010 | |
| contenttype | Fulltext |