Communities surrounding local airports are becoming increasingly concerned about the aircraft pollutants emitted during the landing-takeoff (LTO) cycle, and their potential for negative health effects. Chicago, Los Angeles, Boston and London have all recently been featured in the news regarding concerns over the amount of airport pollution being emitted on a daily basis, and several studies have been published on the increased risks of cancer for those living near airports. There are currently no inexpensive, portable, and unobtrusive sensors that can monitor the spatial and temporal nature of jet engine exhaust plumes. In this work we seek to design a multispectral imaging system that is capable of tracking exhaust plumes during the engine idle phase, with a specific focus on unburned hydrocarbon (UHC) emissions. UHCs are especially potent to local air quality, and their strong absorption features allow them to act as a spatial and temporal plume tracer. Using a Gaussian plume to radiometrically model jet engine exhaust, we have begun designing an inexpensive, portable, and unobtrusive imaging system to monitor the relative amount of pollutants emitted by aircraft in the idle phase. The LWIR system will use two broadband filters to detect emitted UHCs. This paper presents the spatial and temporal radiometric models of the exhaust plume from a typical jet engine used on 737s. We also select filters for plume tracking, and propose an imaging system layout for optimal detectibility. In terms of feasibility, a multispectral imaging system will be two orders of magnitude cheaper than current unobtrusive methods (PTR-MS) used to monitor jet engine emissions. Large-scale impacts of this work will include increased capabilities to monitor local airport pollution, and the potential for better-informed decision-making regarding future developments to airports.
Emily E. Berkson and David W. Messinger, "Pollutant monitoring of aircraft exhaust with multispectral imaging," Proc. SPIE 10008, Remote Sensing Technologies and Applications in Urban Environments, 1000803 (Presented at SPIE Remote Sensing: September 26, 2016; Published: 26 October 2016); https://doi.org/10.1117/12.2242070.
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