A Review of Deterministic, Stochastic and Hybrid Vehicular Exhaust Emission Models

This article reviews vehicular pollution studies carried out at roadways and traffic intersections. Urban corridors are prone to frequent exposures of high pollutant concentrations (episodic conditions). The authors note that in order to predict such ‘episodes’, an air quality model, capable of estimating the entire range (middle and extremes) of pollutant concentration distribution is needed. They review the presently used deterministic, numerical, statistical, statistical distribution, and hybrid vehicular exhaust models, which have demonstrated the ability to predict the entire range of pollutant concentrations in complex dispersion situations with reasonable accuracy The authors report on their development of a hybrid model with improved prediction accuracy. The paper also describes the implications of hybrid models in formulating the Episodic-Urban Air Quality Management Plan (e-UAQMP) which can be used to assist decision makers in designing an air pollution alert system and to provide sensitive members of the population to take protective measures.

Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/49563458
Authors:
- Gokhale, Sharad
- Khare, Mukesh
Publication Date: 2004

Language

English

Media Info

Media Type: Print
Features: Figures; References; Tables;
Pagination: pp 59-74
Serial:
- International Journal of Transport Management
- Volume: 2
- Issue Number: 2
- Publisher: Pergamon
- ISSN: 1471-4051
- Serial URL: http://www.sciencedirect.com/science/journal/14714051

Subject/Index Terms

TRT Terms: Air pollution; Automobiles; Distributions (Statistics); Exhaust gases; Hybrid simulation; Mathematical models; Probability; Statistical analysis; Stochastic processes
Subject Areas: Data and Information Technology; Highways;

Filing Info

Accession Number: 01003008
Record Type: Publication
Files: TRIS, ATRI
Created Date: Aug 5 2005 9:58AM