Causes, Cost Consequences, and Risk Implications of Accidents in U.S. Hazardous Liquid Pipeline Infrastructure
In this paper the causes and consequences of accidents in US hazardous liquid pipelines that result in the unplanned release of hazardous liquids are examined. Understanding how different causes of accidents are associated with consequence measures can provide important inputs into risk management for this (and other) critical infrastructure systems. Data on 1582 accidents related to hazardous liquid pipelines for the period 2002–2005 are analyzed. The data were obtained from the US Department of Transportation’s Office of Pipeline Safety (OPS). Of the 25 different causes of accidents included in the data the most common ones are equipment malfunction, corrosion, material and weld failures, and incorrect operation. This paper focuses on one type of consequence–various costs associated with these pipeline accidents–and causes associated with them. The following economic consequence measures related to accident cost are examined: the value of the product lost; public, private, and operator property damage; and cleanup, recovery, and other costs. Logistic regression modeling is used to determine what factors are associated with nonzero product loss cost, nonzero property damage cost and nonzero cleanup and recovery costs. The factors examined include the system part involved in the accident, location characteristics (offshore versus onshore location, occurrence in a high consequence area), and whether there was liquid ignition, an explosion, and/or a liquid spill. For the accidents associated with nonzero values for these consequence measures (weighted) least squares regression is used to understand the factors related to them, as well as how the different initiating causes of the accidents are associated with the consequence measures. The results of these models are then used to construct illustrative scenarios for hazardous liquid pipeline accidents. These scenarios suggest that the magnitude of consequence measures such as value of product lost, property damage and cleanup and recovery costs are highly dependent on accident cause and other accident characteristics. The regression models used to construct these scenarios constitute an analytical tool that industry decision-makers can use to estimate the possible consequences of accidents in these pipeline systems by cause (and other characteristics) and to allocate resources for maintenance and to reduce risk factors in these systems.