Hazardous Materials Transportation: a Literature Review and an Annotated Bibliography

The hazardous materials transportation poses risks to life, health, property, and the environment due to the possibility of an unintentional release. We present a bibliographic survey on this argument paying particular attention to the road transportation. We attempt to encompass both theoretical and application oriented works. Research on this topic is spread over the broad spectrum of computer science and the literature has an operations research and quantitative risk assessment focus. The models present in the literature vary from simple risk equations to set of differential equations. In discussing the literature, we present and compare the underlying assumptions, the model specifications and the derived results. We use the previous perspectives to critically cluster the papers in the literature into a classification scheme

A framework for modeling risk and emergency response in hazardous materials transportation

Hazardous materials transport is a significant economic activity. Routing is one of the key issues in hazardous materials transport. Cost and risk are primary factors influencing routing. Emergency preparedness is an issue that is common to all of these. Traditionally, risks and emergency preparedness have been addressed as two interdependent issues, but the interactions between them have not been addressed explicitly. This often results in risk estimates that ignore the effect of emergency preparedness; This research presents a framework for quantifying effects of emergency preparedness on risk of hazardous materials transportation. Risk estimates are typically based on the probability of accident, probability of a release given an accident, and consequence. An emergency response factor, {dollar}\beta{dollar}, is introduced to obtain a modified estimate of risk. The modified risk is termed effective risk and considers emergency preparedness. Effective risk is defined as a product of {dollar}\beta{dollar} and initial risk derived using the probabilistic risk methodology. Emergency preparedness is measured in terms of response times and capabilities of initial responders. Initial responders were assumed to be fire units. Travel time is used to represent response times, which were evaluated using a Geographic Information System (GIS) program. Capabilities include personnel availability, personnel training, personal protective equipment, and general control equipment. These were evaluated using a rating scheme. Three indices were introduced to represent response times and capabilities. These are the travel time index, response unit index, and response capability index. These indices were used to estimate emergency response factor; A case study of three major routes I-15, US-95, and US-93 in Clark County, Nevada is presented to illustrate the emergency preparedness based risk assessment methodology. The study shows that the effective risk tends to decrease with emergency preparedness and increase with the lack of it. In metropolitan areas where emergency responders are immediately available, effective risks are lower than the initial risk estimates. For the three routes analyzed, the critical segments identified in the initial risk analysis remained critical, despite the inclusion of emergency preparedness. These were the segments with either high accident rates or population density, or a combination of both. Route segments, with no or relatively poor emergency response capability, which were not initially identified to be high risk have been highlighted in the effective risk estimates. These segments were shown to be as important as those which were identified to be critical. Emergency response is significant in areas where the responders are not available within the 10-minute travel time; Effective risk estimates could support decision and policy making, resource management, developing hazardous materials routing criteria, identifying critical links and areas, addressing questions of equity and risk distribution, and re-evaluating disjoint techniques that are currently being used

Measuring and optimizing accessibility to emergency medical services

Emergency medical services (EMSs) undertake the responsibility of providing rapid medical care to patients suffering from unexpected illnesses or injuries and transferring them to definitive care facilities. This research concerns several research gaps that are associated with different EMS trips, real-time traffic conditions, improving EMS efficiency and equalities. This research aims to develop GIS-based spatial optimization methods to improve service efficiency and equality in EMS systems. Specifically, the research intends to achieve the following goals: (1) to measure spatiotemporal accessibility to EMS; (2) to improve EMS efficiency and provision through spatial optimization approaches; (3) to reduce urban-rural inequalities in EMS accessibility and coverage using spatial optimization approaches. The proposed approaches are applied in three empirical studies in Wuhan, China. To achieve the first objective, the proximity and the enhanced two-step floating catchment method (E-2SFCA) are adopted to evaluate spatiotemporal accessibility. First, the EMS travel time is estimated for the two related trips as an overall EMS journey: one is from the nearest EMS station to the scene (Trip 1), and the other is from the scene to the nearest emergency hospital (Trip 2). Then, the E-2SFCA method is employed to calculate the accessibility score that integrates both geographic accessibility and availability of EMS. Travel time is estimated by using both static road network with standard speed limits and online map service considering real-time traffic. To achieve the second objective, two facility location models are proposed to improve EMS service coverages for two-related trips (Trips 1 and 2). The first model maximizes the amount of demand covered by both ambulance coverage (EMS station – demand) and hospital coverage (demand – hospital). The second model maximizes the amount of demand that can be served by both ambulance coverage and overall coverage (EMS station – demand – hospital). To achieve the third objective, two bi-objective optimization models are developed. The two models have the same primary objective to maximize the total covered demand by ambulance. The second objective is to minimize one of the two inequality measures: one focuses on accessibility of uncovered rural people, and the other concerns the urban-rural inequality in service coverage. For the first empirical study with respect to spatiotemporal access to EMS, different spatial patterns are found for the three trips (two partial trips and the overall trip). Good accessibility to one trip cannot guarantee good accessibility to another trip. In addition, urban-rural inequalities in EMS accessibility and coverage are observed. Finally, it is observed that real-time traffic conditions greatly affect EMS accessibility, particularly in urban districts. Specifically, the accessibility of EMS becomes poor during the morning (7-9 am) and evening peak periods (5-7 pm). For the second empirical study in relation to EMS optimization involving two related trips, the results find that the first proposed model can guarantee that more demand to be covered by both ambulance and hospital coverages than the Maximum Coverage Location Problem (MCLP). The second proposed model can ensure that as many people as possible to be served by both ambulance and overall coverage than the work by ReVelle et al. (1976). For the third empirical study attempting to reduce urban-rural inequality in EMS, the results show that the first bi-objective model can improve EMS accessibility of uncovered rural demand, and the second model can reduce EMS service coverages between urban and rural areas. However, the improvement EMS inequalities between urban and rural areas leads to a cost of a decrease in the total covered population, especially in urban areas. Regarding policy implications, this research suggests that different EMS trips and traffic conditions should be considered when measuring spatial accessibility to EMS. Spatial optimization research can help improving service efficiency and reduce regional equalities in EMS systems. The work presented in this thesis can aid the planning practice of public services like EMS and provide decision support for policymakers