PLAZO VALOR

QRA involves two processes: estimation of factors affecting risk and calculation of risk using a quantitative model (Erkut and Verter, 1995). In the “traditional” risk model, risk is the product of the probability of incident and the consequence of the incident (Erkut et al., 2007). There are also several alternative models that may be used to describe risk (Erkut and Verter, 1998; Erkut and Ingolfsson, 2005). All models, however, rely on estimation of the same two basic components: the probability and the consequence of the incident. In the context of railroad hazardous materials transportation risk, the first component includes the estimation of the probability of a hazardous material release, which is the product of a series of probabilities (Woodward, 1989), i.e. accident rate, probability of car derailment given a train accident, and probability of a hazardous materials release in an accident. The second component concerns the estimation of effects from the hazardous material release. There are various metrics for this, such as the number of fatalities, the number of persons exposed to a release, environmental impact, damage costs, etc. In this section, I focus on literature and studies on estimation of risk parameters of these two components of the QRA model.

2.4.1 Accident Rates and Release Rates

Nayak et al. (1983) developed the procedures for evaluating the probability and impacts of hazardous material accidents in rail transportation and, for the first time, quantified the correlation between the Federal Railroad Administration (FRA) track classes, accident frequencies, and the effect of train speed on accident severity. The analysis focused on track- caused accidents and quantitative estimates were provided in terms of the amount of hazardous material released per accident and the area affected by the releases.

Phillips and Role (1989) described the types of tank cars and their performance in accidents for selected hazardous materials commodities over the 22-year period (1965-1986). In their report, the lading loss data were presented for pressure and non-pressure cars by year and cause of accident. The effectiveness of shelf couplers and head shields on preventing head punctures was specifically considered as well.

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Treichel and Barkan (1993) investigated the relationship between track classes and accident probability and severity in the context of QRA modeling. Following Nayak et al. (1983), they developed both “numerator” and “denominator” data enabling calculations of track- class-specific accident rates for use as a proxy for track quality in risk analysis. They developed accident and derailment rates for U.S. Class-1 railroads and also developed estimates of the average number of cars derailed in mainline freight train accidents by track class and train speed. They mentioned that the conditional probability of release, given a derailment, and the expected quantity spilled, given a release, increase with train speed and track class. Therefore, the risk on a specific track class should not be inferred from accident rates alone but should take into account other factors to allow better estimation of track-class-specific risk.

CCPS (1995) suggested quantitative estimates of various risk parameters, including derailment and accident frequencies for specific track classes, the probability of car derailment given an accident, release probabilities, and the effects of speed on the number of cars derailed and on the release probabilities.

Dennis (1996) provided statistics on accident rate and probability of release given an accident during the 13-year period (1982–1994). The rates, however, were not analyzed by specific track class. He also studied the costs incurred as a result of the presence of hazardous materials and developed risk costs associated with railroad hazardous materials transportation.

Arthur D. Little, Inc. (1996) provided track-class-specific train accident and car

derailment rates for railroad hazardous materials transportation risk analysis, based on Treichel and Barkan (1993). This report also quantified the benefits of various risk reduction options.

Dennis (2002) studied the changes in railroad accident rates from 1983 to 1994. The rate declined substantially following the economic deregulation of railroads. He assessed the

significance of various factors that affected this and concluded that railroad track investment had a statistically significant effect on the decline, while federal regulation had a statistically

insignificant effect on the reduction of track accidents. Furthermore, there was not a statistically significant acceleration or deceleration in the rate of change of the accident rates over the period studied.

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Anderson and Barkan (2004) used Treichel and Barkan’s (1993) results, combined with updated FRA accident data, to develop updated estimates of track-class-specific accident rates. They also conducted sensitivity analyses in order to understand possible track-class-specific change.

Treichel et al. (2006) described a comprehensive statistical analysis of tank car safety performance in FRA-reportable accidents. This study provides regression formulae that can be used to estimate the accident performance of each car configuration and certain major tank car design elements. The report includes statistics on conditional probability of release (CPR) for both mainline and yard accidents, as well as quantity loss amounts and the effect of accident speed on CPR for non-pressure and pressure tank cars.

2.4.2 Consequence of Release

The consequence of a hazardous material release in an accident can be expressed using several metrics, such as human impact (i.e. the number of injuries or fatalities, the number of persons potentially exposed to a release), monetary unit (i.e. costs) due to property damage,

environmental change, and litigation or other forms of financial impact. The following is a brief review of some of the literature related to hazardous materials consequence estimation and modeling.

Birk et al. (1990a, 1990b) developed a computer program to simulate the consequences of a train derailment accident. The program used several models that accounted for train derailment mechanics, flammable liquid spills, fire effects on remote targets, fire impingement on tank cars carrying dangerous commodities, explosion blast over-pressure and thermal radiation, and heavy plume and puff dispersion.

Brown et al. (2000; 2005; 2009) described the development of the values in the table of initial isolation and protective action distances used in the Emergency Response Guidebook (ERG), which is jointly developed by the U.S. Department of Transportation, Transport Canada, and the Secretariat of Communications and Transportation of Mexico (PHMSA, 2004; PHMSA, 2008). The ERG is designed for use by first responders to determine the appropriate level of action during the initial stages of a hazardous materials transportation incident (Brown and Dunn, 2007). It also provides initial isolation and protective action distances for consideration in the event of a hazardous materials release for specific chemicals and scenarios of release. More

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recently, it has been used as a measure of the relative impact of different hazardous materials (Saat, 2009).

Kara et al. (2003) pointed out that using a Geographic Information System (GIS) to compute consequence with population density data may overestimate the population exposure if an algorithm or computation process double-counts the population in an overlapped exposure area of two or more intersecting route segments. Consequently, it may result in the selection of a suboptimal path. They proposed an approach to this problem by developing an algorithm to allow better estimation of population exposure in the transportation network.

Hanna et al. (2008) tested different gas dispersion models that have been widely used to calculate downwind chlorine gas concentrations. The test used the scenarios of release that occurred in Festus, MO; Macdona, TX; and Graniteville, SC. They concluded that the models evaluated closely agreed in the estimates of downwind dispersion when given the same source emission terms for the scenarios and assumed conditions.

Other than human population units, risk consequences can also be expressed in monetary units, i.e. risk cost. The following are some information sources on cost estimation that may be useful in hazardous materials risk analyses.

In January 1993, the U.S. DOT adopted a guidance memorandum called "Treatment of Value of Life and Injuries in Preparing Economic Evaluations", with recommended economic values to be used in the departmental regulatory and investment analyses. Viscusi and Aldy (2003) provided a comprehensive review of the value of statistical life (VSL). They also provided a detailed discussion of the policy applications of VSL estimates and other related issues. Alberini (2005) explained that the VSL is the rate at which people are prepared to trade off income for a reduction in their risk of dying, and that it is a key input in computing the mortality benefits of environmental and safety policies that save lives. In short, VSL is the trade-off between money and fatality risks (Viscusi and Aldy, 2003). According to the U.S. DOT (2008), the current estimate of the VSL in the U.S. is $5.8 million.