LIDAR System for Area Sensing of Vehicle Emissions: Final Evaluation Report

Abstract

This report presents an assessment of the effectiveness of an elastic LIDAR system (wavelength of 1.06 um) for wide-area remote sensing of pollutant concentrations associated with particulate plumes near urban roadways. Traditional point-sampling instruments were also used to measure mass concentrations of particulate matter and carbon monoxide (CO) concentrations near the roadways. The size distribution of the particulate matter was also measured, and variations in the size-resolved particle concentrations were compared to the LIDAR signal. We found that the LIDAR signal was most sensitive to the concentration particles whose characteristic dimensions were slightly larger than the wavelength of the laser used, and that a relation exists between the two. Hence, when used at low elevations near roadways, the 1.06 um wavelength LIDAR system located plumes of particles whose aerodynamic diameters fell in the 1-5 um size range, and tracked changes in their concentrations. Particles in this size range lie primarily in the coarse size range of respirable aerosols, and are readily made airborne by vehicle-induced air motion and thermal drafts associated with pavement and vehicle exhaust. The bulk of this report summarizes the operating characteristics of the LIDAR system; issues regarding field deployment, including eye safety, reliability, and operator training; requirements for image display and interpretation; and correlations between the LIDAR signal, pollutant concentrations, and traffic. The influence of varying weather conditions, primarily wind speed, direction, and relative humidity, is discussed. Recommendations for further development are also given, including comments on the feasibility of fine particle LIDAR and species specific LIDARS. Firm conclusions regarding the air quality impacts associated with the operation of a portable traffic management system designed to minimize traffic congestion cannot be drawn at this time due to uncertainties associated with the effectiveness of the traffic management system and large variabilities introduced by varying weather and traffic conditions.