Remote Sensing Measurements for the E-100a Longitudinal Emission Pilot Study

Sponsor: Coordinating Research Council

PI: Claudio Mazzoleni

Gases and aerosols emitted by vehicles have potential effects on human health, plants and animals, air quality, artistic and historic buildings, visibility and climate. Uncertainties in the pollutants emitted by vehicles stem from many complicating and confounding factors including for example, but not limited to: a) wide variety of vehicle and engine types; b) vehicle use and maintenance; c) vehicle operating conditions; d) vehicle age; e) fuel type and quality; f) owners’ driving habits; g) weather conditions; h) road conditions; i) enforcements of inspection and maintenance (I/M) programs or other emission control programs.

Due to the large number of parameters and the wide variability for each, it is very challenging to obtain a representative and statistically relevant sample of vehicle emission measurements. To make the task even more formidable, the emission distribution across the vehicle fleet is often strongly skewed, making a few, hard-to-find vehicles responsible for the largest fraction of the total on-road fleet exhaust emissions.  The emission distribution skewness has been show to be especially severe for carbon monoxide and PM emissions – often 10% of vehicles contribute more than 70% of the total fleet emissions for passenger cars. Therefore, normal statistical approaches are ineffective and inaccurate. To provide a correct picture of the impact of a vehicle fleet and to stratify emissions by different confounding variables, a measurement method must accurately capture the tail of the emission distribution. Among the many techniques available for the vehicle emission measurement, remote sensing presents a unique set of advantages. First, remote sensing offers the possibility to collect data for thousands of vehicles at a reasonable cost with realistic time and human investments. Second, remote sensing is the only currently available technique that can collect data representative of a large and realistic ensemble of individual vehicles, at the same time maintaining the specificity of “single vehicle” emission measurements.

Final Report:  E100a_Pilot_Study_23Aug2011_Final

Claudio Mazzoleni
Claudio Mazzoleni