Development of Remote Sensing Instrumentation for NO_x and PM Emissions from Heavy Duty Trucks

摘要

This paper describes an effort under way at Oak Ridge National Laboratory to develop prototype instruments to remotely and non-intrusively measure the NOx and particulate matter (PM) emissions from heavy trucks in actual use on a roadway. An ultraviolet (UV) absorption method and a modified LIDAR method are being employed to measure NOx and PM concentrations, respectively, in the exhaust plumes of moving trucks. To couple the concentration measurements to the truck on a gram-per-mile basis, an innovative approach to determining engine operating conditions with remote sensing is being employed. This is accomplished by using sensitive listening equipment to acquire acoustic signatures as the truck passes. Acoustic signature analysis will devolve data about the truck's operating parameters, such as engine speed, turbine speed, and number of cylinders. The combined results will be used to make estimates of the instantaneous exhaust flow rate, which, when coupled with the emission concentration measurements, vehicle speed, acceleration, and load, lead to emissions data in terms of grams-per-mile. These three technologies represent extensions and modifications of existing measurement sciences into this new application, and much of the challenge is the development of algorithms for interpreting data from each. This paper discusses the progress to date of a two-year project that began in October 2002. Accordingly, the presentation accompanying this paper will include more information and more progress than presented here. This effort is part of a larger project concept dealing with truck emissions and their impacts on local air quality. The Watt Road Environmental Laboratory Initiative is a joint effort between ORNL and the University of Tennessee, Knoxville to develop a field laboratory for comprehensive studies of truck emissions in a 2.5-mile corridor along Interstate 40 in Knox County, Tennessee. This initiative is also described briefly in the paper.