TITLE:
Statistical Model for Estimating Carbon Dioxide Emissions from a Light-Duty Gasoline Vehicle
AUTHORS:
Benjamin Afotey, Melanie Sattler, Stephen P. Mattingly, Victoria C. P. Chen
KEYWORDS:
Carbon Dioxide; Model; On-Board Emissions Measurement System; Mobile Sources
JOURNAL NAME:
Journal of Environmental Protection,
Vol.4 No.8A,
August
8,
2013
ABSTRACT: The objective of this research was
development of a statistical model for estimating vehicle tailpipe emissions of
carbon dioxide (CO2). Forty hours of second-by-second emissions data
(144,000 data points) were collected using an On-Board emissions measurement
System (Horiba OBS-1300) installed in a 2007 Dodge Charger car. Data were
collected for two roadway types, arterial and highway, around Arlington, Texas,
and two different time periods, off peak and peak (both a.m. and p.m.).
Multiple linear regression and SAS software were used to build emission models
from the data, using predictor variables of velocity, acceleration and an
interaction term. The arterial model explained 61% of the variability in the
emissions; the highway model explained 27%. The arterial model in particular
represents a reasonably good compromise between accuracy and ease of use. The
arterial model could be coupled with velocity and acceleration profiles
obtained from a micro-scale traffic simulation model, such as CORSIM, or from
field data from an instrumented vehicle, to estimate percent emission
reductions associated with local changes in traffic system operation or management.