Author/Authors :
R. Smit*، نويسنده , , A.L. Brown، نويسنده , , Y.C. Chan، نويسنده ,
Abstract :
Road transport emission and fuel consumption models are currently used extensively to predict levels of air
pollution along roadway links and networks. This paper examines how, and to what extent, models which
are currently used to predict emissions and fuel consumption from road traffic include the effects of
congestion. A classification framework is presented in which a key factor, driving pattern, connects emissions
to congestion. Prediction of the effects of different driving patterns in emission models is generally
restricted to certain aspects of modelling, i.e. hot-running emissions of regulated pollutants. As a consequence,
the effects of congestion are only partially incorporated in the predictions. Themajority of emission
models explicitly incorporate congestion in themodelling process, but for one important family of emission
models, namely average speed models, this could not be determined directly. Re-examination of the (lightduty)
driving patterns on which three average speed models (COPERT, MOBILE, EMFAC) are based, shows
that it is likely that congestion is represented in these patterns. Since (hot-running) emission factors are
based on these patterns, this implies that the emission factors used in these emission models also reflect
different levels of congestion. Congestion is thus indirectly incorporated in these models. It is recommended,
that, in order to get more accurate (local) emission predictions and to achieve correct application
in particular situations, it is important to improve current average speed models by including a congestion
algorithm, or alternatively, at least provide information on the level of congestion in the driving patterns on
which these models are based and recommendations on what applications the models are suitable for.