Qualitative and Quantitative Analyses of Automotive Exhaust Plumes for Remote Emission Sensing Application Using Gas Schlieren Imaging Sensor System

Abstract

Remote emission sensing (RES) is a state-of-the-art technique for monitoring thousands of vehicles on the road every day to detect high emitters. Modern commercial RES systems use absorption spectroscopy to measure the ratio of pollutants to CO2 from vehicle exhaust gases. In this work, we present an approach to enable direct concentration measurements by spectroscopic techniques in RES through measurement of the absorption path length. Our gas schlieren imaging sensor (GSIS) system operates on the principle of background-oriented schlieren (BOS) imaging in combination with advanced image processing and deep learning techniques to calculate detected exhaust plume sizes. We performed a qualitative as well as a quantitative analysis of vehicle exhaust and plume dimensions with the GSIS system. We present the system details and results from the GSIS system in the lab in comparison to a BOS model based on flow simulations, the results from characterization measurements in the lab with defined gas mixtures and temperatures, and the results from measurements on the road from different vehicles.