Development and evaluation of SBLINE, a suite of models for the prediction of pollution concentrations from vehicles in urban areas

被引:13
作者
Namdeo, AK [1 ]
Colls, JJ [1 ]
机构
[1] UNIV NOTTINGHAM, LOUGHBOROUGH LE12 5RD, LEICS, ENGLAND
关键词
urban air pollution; emission factors; vehicles; dispersion modelling;
D O I
10.1016/0048-9697(96)05224-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The assessment of air quality impacts from roadways is a major concern to urban planners, developers, health officials and engineers. This paper describes the development of a suite of models, called SBLINE, for prediction of pollution concentrations from vehicles in urban road networks. The first component of the suite is ROADFAC, an emission model for calculating emission rates for a road link with known vehicle fleet structure and operational details. ROADFAC can also calculate modal emission rates, caused by deceleration, idle, acceleration and cruise operational modes, by determining queue length and vehicle delay from traffic volume and signal phasing information. The other components of SBLINE are two dispersion models, called NOTLINE and CPB, for prediction of pollution concentrations contributed by different roadlinks in the network. These models use site geometry, meteorology, and traffic emissions calculated by ROADFAC to predict pollutant concentrations. The contribution from a given link is calculated by using NOTLINE if that link is situated in simple topography, or CPB is run if the link is inside a canyon or a cut-section. Finally, cumulative concentrations at any receptor location are calculated by adding the contributions from all roadlinks. SBLINE can be applied to any urban network of roads, with roadlinks located in either simple topography or street canyons. The program has been evaluated in one region of Leicester in the UK. The region represents a typical urban network of roads with some roads located in plain topography and some inside medium size canyons. Observed values of pollutant concentrations an compared with predictions made from detailed measurements of the vehicle population parameters, meteorology, and local street and building topography. Well-established statistical techniques have been used to show the potential of SBLINE for application to other road networks.
引用
收藏
页码:311 / 320
页数:10
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