Remote sensing data and a potential model of vehicle exhaust emissions

Journal Article · Tue Nov 01 04:00:00 EST 1994 · Journal of the Air and Waste Management Association

OSTI ID:62287

Stephens, R D ^[1]

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1. General Motors Research and Development Center, Warren, MI (United States)

In June 1991, General Motors Research and Development Center (GMR&D) participated in a remote sensing study conducted by the California Air Resources Board and the U.S. Environmental Protection Agency. During this study, the GMR&D remote sensor was used to measure the carbon monoxide (CO) and hydrocarbon (HC) emissions from approximately 15,000 vehicles. The vehicle type (passenger car, light-duty truck, or medium/heavy-duty truck), manufacturer, and model year were identified for each vehicle by acquiring registration data from the state of California. Analyses were performed separately for each vehicle type and for passenger cars by separate model years. The data indicate that the passenger cars with the highest 10% of CO emissions generated approximately 58% of the total CO from all cars. Similarly, the 10% highest HC-emitting cars generated 65% of the total HC from cars. It was found that for each model year of vehicle, the distribution of emission concentrations followed a logarithmic relationship. The logarithmic functions that describe these relationships can be used to estimate the fraction of vehicles that emitted at or above any given concentration of CO or HC. However, these logarithmic functions only describe measured distributions for vehicles emitting more than 1% CO and 0.015% HC. 13 refs., 9 figs., 8 tabs.

• OSTI ID: 62287
• Journal Information: Journal of the Air and Waste Management Association, Journal Name: Journal of the Air and Waste Management Association Journal Issue: 11 Vol. 44; ISSN JAWAEB; ISSN 1047-3289
• Country of Publication: United States
• Language: English

Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
33 ADVANCED PROPULSION SYSTEMS
AIR POLLUTION CONTROL
AUTOMOTIVE FUELS
CARBON MONOXIDE
CHEMICAL COMPOSITION
EXHAUST GASES
GASOLINE
HYDROCARBONS
NUMERICAL DATA
REGRESSION ANALYSIS
REMOTE SENSING
US EPA