Accidental release of chlorine in Chicago: Coupling of an exposure model with a Computational Fluid Dynamics model

The adverse health effects of the release of hazardous substances into the atmosphere continue being a matter of concern, especially in densely populated urban regions. Emergency responders need to have estimates of these adverse health effects in the local population to aid planning, emergency response, and recovery efforts. For this purpose, models that predict the transport and dispersion of hazardous materials are as necessary as those that estimate the adverse health effects in the population. In this paper, we present the results obtained by coupling a Computational Fluid Dynamics model, FLACS (FLame ACceleration Simulator), with an exposure model, DDC (Damage Differential Coupling). This coupled model system is applied to a scenario of hypothetical release of chlorine with obstacles, such as buildings, and the results show how it is capable of predicting the atmospheric dispersion of hazardous chemicals, and the adverse health effects in the exposed population, to support decision makers both in charge of emergency planning and in charge of real-time response. The results obtained show how knowing the influence of obstacles in the trajectory of the toxic cloud and in the diffusion of the pollutants transported, and obtaining dynamic information of the potentially affected population and of associated symptoms, contribute to improve the planning of the protection and response measures.Centro de Investigaciones del MedioambienteUniversidad de Buenos Aire

Plume Dispersion Modeling of Chlorine Gas Released Due to Ballistic Attack on Chlorine-Carrying Railway Tanker

Hazardous dense gases such as chlorine are often transported throughout the United States in their liquid form in pressurized railway tankers. These tankers can hold up to 90 tons of liquid chlorine. A high-powered, ballistic attack on a chlorine-carrying tanker could cause devastating outcomes for the surrounding population and environment. This particular terrorist attack was modeled and analyzed by varying a large number of weather parameters and by varying terrain in order to provide specific concentration data at different distances from the source. Data was compiled to provide first responders with a reliable reference for such an emergency so that evacuations and mitigation could be done effectively. The Hazard Predication and Assessment Capability (HPAC) model provided by the Defense and Threat Reduction Agency (DTRA) and the Areal Locations of Hazardous Atmospheres (ALOHA) model provided by the Environmental Protection Agency (EPA) were verified against actual experiments and plume theories and were used to model the chlorine gas plumes resulting from such an attack. Locations of interest were Chicago, IL due to its urbanized area and skyscrapers and Jackson, MS because of its relatively flat terrain and wooded areas. The varying of the locations provided different terrain factors. This research was not only limited to worst-case scenarios, but it also took into account other, less disastrous scenarios in order to provide useful and practical data for first responders. The goal was to reduce the preliminary work first responders must perform before reacting to a ballistic attack on a chlorine-carrying railway tanker

Tier 1 Highway Security Sensitive Material Dynamic Risk Management

Each year, over 2 billion tons of hazardous materials are shipped in the United States, with over half of that being moved on commercial vehicles. Given their relatively poor or nonexistent defenses and inconspicuousness, commercial vehicles transporting hazardous materials are an easy target for terrorists. Before carriers or security agencies recognize that something is amiss, their contents could be detonated or released. From 2006 to 2015, the U.S. Department of Transportation’s Pipeline and Hazardous Materials Safety Administration (PHMSA) recorded 144,643 incidents involving a release of hazardous materials. Although there were no known instances of terrorism being the cause, accidental releases involving trucks carrying hazardous materials are not an uncommon occurrence. At this time, no systems have been developed and operationalized to monitor the movement of vehicles transporting hazardous materials. The purpose of this dissertation is to propose a comprehensive risk management system for monitoring Tier 1 Highway Security Sensitive Materials (HSSMs) which are shipped aboard commercial vehicles in the U.S. Chapter 2 examines the history and current state of hazardous materials transportation. Since the late 19th century, the federal government often introduced new regulations in response to hazardous materials incidents. However, over the past 15 years few binding policies or legislation have been enacted. This demonstrates that government agencies and the U.S. Congress are not inclined to introduce new laws and rules that could hamper business. In 2003, the Federal Motor Carrier Safety Administration (FMCSA) and other agencies led efforts to develop a prototype hazardous materials tracking system (PHTS) that mapped the location of hazardous materials shipments and quantified the level of risk associated with each one. The second half of this chapter uses an in-­‐depth gap analysis to identify deficiencies and demonstrate in what areas the prototype system does not comply with government specifications. Chapter 3 addresses the lack of customized risk equations for Tier 1 HSSMs and develops a new set of risk equations that can be used to dynamically evaluate the level of risk associated with individual hazardous materials shipments. This chapter also discusses the results of a survey that was administered to public and private industry stakeholders. Its purpose was to understand the current state of hazardous materials regulations, the likelihood of hazardous materials release scenarios, what precautionary measures can be used, and what influence social variables may have on the aggregate consequences of a hazardous materials release. The risk equation developed in this paper takes into account the survey responses as well as those risk structures already in place. The overriding goal is to preserve analytical tractability, implement a form that is usable by federal agencies, and provide stakeholders with accurate information about the risk profiles of different vehicles. Due to congressional inaction on hazardous 3 materials transportation issues, securing support from carriers and other industry stakeholders is the most viable solution to bolstering hazardous materials security. Chapter 4 presents the system architecture for The Dynamic Hazardous Materials Risk Assessment Framework (DHMRA), a GIS-­‐based environment in which hazardous materials shipments can be monitored in real time. A case study is used to demonstrate the proposed risk equation; it simulates a hazardous materials shipment traveling from Ashland, Kentucky to Philadelphia, Pennsylvania. The DHMRA maps risk data, affording security personnel and other stakeholders the opportunity to evaluate how and why risk profiles vary across time and space. DHRMA’s geo-­‐fencing capabilities also trigger automatic warnings. This framework, once fully implemented, can inform more targeted policies to enhance the security of hazardous materials. It will contribute to maintaining secure and efficient supply chains while protecting the communities that live nearest to the most heavily trafficked routes. Continuously monitoring hazardous materials provides a viable way to understand the risks presented by a shipment at a given moment and enables better, more coordinated responses in the event of a release. Implementation of DHRMA will be challenging because it requires material and procedural changes that could disrupt agency operations or business practices — at least temporarily. Nevertheless, DHRMA stands ready for implementation, and to make the shipment of hazardous materials a more secure, safe, and certain process. Although DHMRA was designed primarily with terrorism in mind, it is also useful for examining the impacts of accidental hazardous materials releases. Future iterations of DHMRA could expand on its capabilities by incorporating modeling data on the release and dispersion of toxic gases, liquids, and other substances

Lost in optimisation of water distribution systems? A literature review of system operation

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Optimisation of the operation of water distribution systems has been an active research field for almost half a century. It has focused mainly on optimal pump operation to minimise pumping costs and optimal water quality management to ensure that standards at customer nodes are met. This paper provides a systematic review by bringing together over two hundred publications from the past three decades, which are relevant to operational optimisation of water distribution systems, particularly optimal pump operation, valve control and system operation for water quality purposes of both urban drinking and regional multiquality water distribution systems. Uniquely, it also contains substantial and thorough information for over one hundred publications in a tabular form, which lists optimisation models inclusive of objectives, constraints, decision variables, solution methodologies used and other details. Research challenges in terms of simulation models, optimisation model formulation, selection of optimisation method and postprocessing needs have also been identified

Nuclear Power

The world of the twenty first century is an energy consuming society. Due to increasing population and living standards, each year the world requires more energy and new efficient systems for delivering it. Furthermore, the new systems must be inherently safe and environmentally benign. These realities of today's world are among the reasons that lead to serious interest in deploying nuclear power as a sustainable energy source. Today's nuclear reactors are safe and highly efficient energy systems that offer electricity and a multitude of co-generation energy products ranging from potable water to heat for industrial applications. The goal of the book is to show the current state-of-the-art in the covered technical areas as well as to demonstrate how general engineering principles and methods can be applied to nuclear power systems

Quantitative structure-property relationships for predicting group IIB metal binding by organic ligands

Mercury (Hg), cadmium (Cd), and zinc (Zn) in the environment are all of toxicological and environmental concern, and the pollution of natural waters by any of these three elements is most serious. Mercury is the most environmentally concerning of the three because of the neurotoxin species monomethylmercury produced in aquatic systems through the methylation of Hg2+ by aquatic microorganisms. An important chemical process in natural waters that limits the availability of mercury for methylation is the binding of Hg(II) by natural organic matter (NOM). These associations are exceptionally strong, and as NOM is ubiquitous in aquatic environments, estimating equilibrium constants for Hg(II) binding to NOM in natural waters is important. Cadmium is moderately toxic to all organisms, and skeletal damage caused by exposure to cadmium-contaminated water has been reported. Also high concentrations of zinc that are toxic or even lethal to organisms have been observed in natural waters. As the free ion forms of cadmium and zinc in natural waters are thought to be most toxic, Cd(II) and Zn(II) complexation by NOM and estimating the complexation equilibrium constants are, similarly to Hg(II), of interest. With experimental determination of M(II)-NOM (M = Hg, Cd, Zn) binding constants being costly and time consuming, it is desirable to estimate those constants without the benefit of additional experimental data. This work uses QSPRs (Quantitative Structure-Property Relationships) to predict binding constants from hypothetical structures of NOM molecules. For the first time, to our knowledge, a QSPR for predicting Hg(II) complexation by organic ligands has been developed. Also two QSPRs for predicting Cd(II) and Zn(II) complexation by organic ligands, that had been developed earlier, have been improved to be capable of predicting the binding of Cd(II) and Zn(II) to thiol-containing molecules. Most of the compounds used in the calibration data sets of the three QSPRs contained some or all of carboxylate, amine, and thiol ligand groups. The Hg(II), Cd(II), and Zn(II) QSPRs respectively have standard error of prediction (Spred) values of 1.60, 0.935, and 0.984 log units and describe 96.5%, 93.1%, and 93.4% of the variability in data. The most noteworthy observation in the developed QSPRs was the exceptionally high affinity Hg(II) had for thiols. Although thiols form a very small fraction of NOM, this binding is considerably important because of its strength. This work also presents certain potential applications of the developed QSPRs in predicting M(II)-NOM binding as well as predicting M(II) binding to organic molecules which would be synthesized for M(II) remediation and chelation therapy