Risks of transporting dangerous goods : South Durban case study.

Abstract

Industry both consumes and creates an abundance of dangerous goods, which must be transported from producers to end-users. This creates opportunities for incidents, including traffic accidents, which could release poisonous, corrosive, flammable or carcinogenic substances into the environment. Releases of dangerous goods at a location may pose a significant threat to the health of the neighbouring population. The Durban South Basin, with its hazardous mix of heavy industrial, employment and residential areas, was chosen as the case study for research into the risks associated with the transportation of dangerous goods. High levels of traffic flow occur in this region and significant volumes of dangerous goods are transported on the roads within the basin. The objectives of this investigation were to: develop a methodology that may be applied to estimate the likelihood and consequences of releases of dangerous goods due to road accidents; and to evaluate the usefulness of this methodology by applying it to estimate the risks posed to the people residing in, working in and travelling through the Durban South Basin. The literature pertaining to risk assessment of dangerous goods transport was examined. A review was undertaken of the current state of the art and the theory and methodology used by previous researchers. As intersections provide greater opportunities for vehicles to be involved in accidents, traffic surveys were conducted at selected intersections within the Durban South Basin in order to obtain an indication of the flow of dangerous goods vehicles and the types of dangerous goods being transported through these locations. Two approaches were utilised to estimate the likelihood of dangerous goods accidents and releases at intersections: a deterministic model and an innovative method based on Monte Carlo simulation. Dispersion modelling and geographic information systems were integrated to estimate the impacts of accidental releases of dangerous goods at intersections. Queuing analysis was combined with dispersion modelling to estimate the risks posed to road users from dangerous goods releases. The investigation verified that dangerous goods transportation risk assessment could be performed even when there are substantial data uncertainties. Furthermore, in comparison to the deterministic approach typically used in transportation studies, Monte Carlo simulation facilitates a deeper understanding of the nature and distribution of dangerous goods accident risk. The results suggest that although dangerous goods accidents and releases are infrequent, the potential exists for very serious incidents involving large numbers of injuries.