01126754

Component

Road traffic emission is accounted for high proportions of many harmful pollutants. Exact prediction of pollution episodes occurrence, strength and duration is a formidable problem due to the combination of many complex physical and chemical processes involved. This underpins the need for the development of sophisticated statistical methods in order to facilitate prediction of high pollution concentrations and to understand better their cause. In this paper, joint extremes of ozone (O3), nitrogen dioxide (NO2) and nitrogen oxide (NO) have been investigated using the peaks-over-threshold (POT) approach extended by treating the parameters of the generalized Pareto distribution as certain functions of traffic and meteorological factors (such as traffic flow, speed, air temperature, relative humidity, wind speed and wind direction). The impact of these factors on the joint distribution of extreme values has been estimated, and in particular combinations of traffic and meteorological conditions that determine persistent interdependence between extremes of different pollutants have been identified using the copula method. Due to the complexity of the model, the Markov Chain Monte Carlo (MCMC) method has been employed for the parameter estimation. Appropriate goodness-of-fit tests confirm that the model proposed in this study provides accurate estimation of joint extremes in the air pollution concentrations.

01120148

09-3484

English

13p

2009

Transportation Research Board 88th Annual Meeting

DVD

Figures (5) ; References (31) ; Tables (1)

Air pollution; Air quality management; Environment; Goodness of fit; Meteorology; Monte Carlo method; Multivariate analysis; Nitrogen oxides; Ozone; Pollutants

Environment; Highways; I15: Environment

Transportation Research Board Annual Meeting 2009 Paper #09-3484

TRIS, TRB

Jan 30 2009 7:54PM