Risk assessment of major hazards and its application in urban planning: a case study

With the rapid development of industry in China, the number of establishments that are proposed or under construction is increasing year by year, and many are industries that handle flammable, explosive, toxic, harmful, and dangerous substances. Accidents such as fire, explosion, and toxic diffusion inevitably happen. Accidents resulting from these major hazards in cities cause a large number of casualties and property losses. It is increasingly important to analyze the risk of major hazards in cities realistically and to suitably plan and utilize the surrounding land based on the risk analysis results, thereby reducing the hazards. A theoretical system for risk assessment of major hazards in cities is proposed in this article, and the major hazard risk for the entire city is analyzed quantitatively. Risks of various major accidents are considered together, superposition effect is analyzed, individual risk contours of the entire city are drawn out, and the level of risk in the city is assessed using "as low as reasonably practicable" guidelines. After the entire city's individual risk distribution is obtained, risk zones are divided according to corresponding individual risk value of HSE, and land-use planning suggestions are proposed. Finally, a city in China is used as an example to illustrate the risk assessment process of the city's major hazard and its application in urban land-use planning. The proposed method has a certain theoretical and practical significance in establishing and improving risk analysis of major hazard and urban land-use planning. On the one hand, major urban public risk is avoided; further, the land is utilized in the best possible way in order to obtain the maximum benefit from its use.     

Cost‐Benefit Analysis of Passive Fire Protections in Road LPG Transportation

The cost‐benefit evaluation of passive fire protection adoption in the road transport of liquefied petroleum gas (LPG) was investigated. In a previous study, mathematical simulations of real scale fire scenarios proved the effectiveness of passive fire protections in preventing the “fired” boiling liquid expanding vapor explosion (BLEVE), thus providing a significant risk reduction. In the present study the economical aspects of the adoption of fire protections are analyzed and an approach to cost‐benefit analysis (CBA) is proposed. The CBA model is based on the comparison of the risk reduction due to fire protections (expressed in monetary terms by the value of a statistical life) and the cost of the application of fire protections to a fleet of tankers. Different types of fire protections were considered, as well as the possibility to apply protections to the entire fleet or only to a part of it. The application of the proposed model to a real‐life case study is presented and discussed. Results demonstrate that the adoption of passive fire protections on road tankers, though not compulsory in Europe, can be economically feasible, thus representing a concrete measure to achieve control of the “major hazard accidents” cited by the European legislation.     

Households' Perceived Personal Risk and Responses in a Multihazard Environment

This study proposed and tested a multistage model of household response to three hazards—flood, hurricane, and toxic chemical release—in Harris County Texas. The model, which extends Lindell and Perry's (1992, 2004) Protective Action Decision Model, proposed a basic causal chain from hazard proximity through hazard experience and perceived personal risk to expectations of continued residence in the home and adoption of household hazard adjustments. Data from 321 households generally supported the model, but the mediating effects of hazard experience and perceived personal risk were partial rather than complete. In addition, the data suggested that four demographic variables—gender, age, income, and ethnicity—affect the basic causal chain at different points.     

Modeling the Cost Effectiveness of Fire Protection Resource Allocation in the United States: Models and a 1980–2014 Case Study

The estimated cost of fire in the United States is about $329 billion a year, yet there are gaps in the literature to measure the effectiveness of investment and to allocate resources optimally in fire protection. This article fills these gaps by creating data‐driven empirical and theoretical models to study the effectiveness of nationwide fire protection investment in reducing economic and human losses. The regression between investment and loss vulnerability shows high R² values (≈0.93). This article also contributes to the literature by modeling strategic (national‐level or state‐level) resource allocation (RA) for fire protection with equity‐efficiency trade‐off considerations, while existing literature focuses on operational‐level RA. This model and its numerical analyses provide techniques and insights to aid the strategic decision‐making process. The results from this model are used to calculate fire risk scores for various geographic regions, which can be used as an indicator of fire risk. A case study of federal fire grant allocation is used to validate and show the utility of the optimal RA model. The results also identify potential underinvestment and overinvestment in fire protection in certain regions. This article presents scenarios in which the model presented outperforms the existing RA scheme, when compared in terms of the correlation of resources allocated with actual number of fire incidents. This article provides some novel insights to policymakers and analysts in fire protection and safety that would help in mitigating economic costs and saving lives.     

Murphy Scale: A locational equivalent intensity scale for hazard events

Empirical cross-hazard analysis and prediction of disaster vulnerability, resilience, and risk requires a common metric of hazard strengths across hazard types. In this paper, the authors propose an equivalent intensity scale for cross-hazard evaluation of hazard strengths of events for entire durations at locations. The proposed scale is called the Murphy Scale, after Professor Colleen Murphy. A systematic review and typology of hazard strength metrics is presented to facilitate the delineation of the defining dimensions of the proposed scale. An empirical methodology is introduced to derive equivalent intensities of hazard events on a Murphy Scale. Using historical data on impacts and hazard strength indicators of events from 2013 to 2017, the authors demonstrate the utility of the proposed methodology for computing the equivalent intensities for earthquakes and tropical cyclones. As part of a new area of research called hazard equivalency, the proposed Murphy Scale paves the way toward creating multi-hazard hazard maps. The proposed scale can also be leveraged to facilitate hazard communication regarding past and future local experiences of hazard events for enhancing multi-hazard preparedness, mitigation, and emergency response.     

An Exact Analysis of the Multistage Model Explaining Dose-Response Concavity

The traditional multistage (MS) model of carcinogenesis implies several empirically testable properties for dose-response functions. These include convex (linear or upward-curving) cumulative hazards as a function of dose; symmetric effects on lifetime tumor probability of transition rates at different stages; cumulative hazard functions that increase without bound as stage-specific transition rates increase without bound; and identical tumor probabilities for individuals with identical parameters and exposures. However, for at least some chemicals, cumulative hazards are not convex functions of dose. This paper shows that none of these predicted properties is implied by the mechanistic assumptions of the MS model itself. Instead, they arise from the simplifying "rare-tumor" approximations made in the usual mathematical analysis of the model. An alternative exact probabilistic analysis of the MS model with only two stages is presented, both for the usual case where a carcinogen acts on both stages simultaneously, and also for idealized initiation-promotion experiments in which one stage at a time is affected. The exact two-stage model successfully fits bioassay data for chemicals (e.g., 1,3-butadiene) with concave cumulative hazard functions that are not well-described by the traditional MS model. Qualitative properties of the exact two-stage model are described and illustrated by least-squares fits to several real datasets. The major contribution is to show that properties of the traditional MS model family that appear to be inconsistent with empirical data for some chemicals can be explained easily if an exact, rather than an approximate model, is used. This suggests that it may be worth using the exact model in cases where tumor rates are not negligible (e.g., in which they exceed 10%). This includes the majority of bioassay experiments currently being performed.     

An Empirical Model for Managing Quality in the Electronics Industry

Much of the empirical research in the past two decades has suggested that quality management (QM) is context dependent. This research develops an empirical QM model in a technology‐based sector—electronics manufacturing. Based on quantitative and qualitative investigations of 225 electronics firms in Hong Kong and the Pearl River Delta (PRD) region of China, a path analytic model is developed. The empirical model shows that a typical quality management system (QMS) in the electronics industry is composed of four major modules, namely leadership, cultural elements, operational support systems, and process management. These modules create a series of chain effects on organizational performance, rather than acting as parallel elements with an equal impact. By quantifying their effects on organizational performance and comparing the model to others in the literature, we identify those QM constructs that are context dependent. In electronics manufacturing, process management and customer focus are more important than other elements (e.g., cultural factors) for garnering business results. This study contributes to contingency theory and research by identifying the key constructs and their relationships in a competitive, volatile, and technology‐based industry with complex supply networks.     

A Monte Carlo Analysis of Health Risks from PCB-Contaminated Mineral Oil Transformer Fires

The objective of this study is the estimation of health hazards due to the inhalation of combustion products from accidental mineral oil transformer fires. Calculations of production, dispersion, and subsequent human intake of polychlorinated dibenzofurans (PCDFs) provide us with exposure estimates. PCDFs are believed to be the principal toxic products of the pyrolysis of polychlorinated biphenyls (PCBs) sometimes found as contaminants in transformer mineral oil. Cancer burdens and birth defect hazard indices are estimated from population data and exposure statistics. Monte Carlo-derived variational factors emphasize the statistics of uncertainty in the estimates of risk parameters. Community health issues are addressed and risks are found to be insignificant.     

Causation Analysis of Risk Coupling of Gas Explosion Accident in Chinese Underground Coal Mines

The coal mine production industry is a complex sociotechnical system with interactive relationships among several risk factors. Currently, causation analysis of gas explosion accidents is mainly focused on the aspects of human error and equipment fault, while neglecting the interactive relationships among risk factors. A new method is proposed through risk coupling. First, the meaning of risk coupling of a gas explosion is defined, and types of risk coupling are classified. Next, the coupled relationship and coupled effects among risk factors are explored through combining the interpretative structural modeling (ISM) and the NK model. Twenty‐eight representative risk factors and 16 coupled types of risk factors are obtained through analysis of 332 gas explosion accidents in coal mines in China. Through the application of the combined ISM–NK model, an eight‐level hierarchical model of risk coupling of a gas explosion accident is established, and the coupled degrees of different types of risk coupling are assessed. The hierarchical model reveals that two of the 28 risk factors, such as state policies, laws, and regulations, are the root risk factors for gas explosions; nine of the 28 risk factors, such as flame from blasting, electric spark, and local gas accumulation, are direct causes of gas explosions; whereas 17 of the risk factors, such as three‐violation actions, ventilation system, and safety management, are indirect ones. A quantitative analysis of the NK model shows that the probability of gas explosion increases with the increasing number of risk factors. Compared with subjective risk factors, objective risk factors have a higher probability of causing gas explosion because of risk coupling.     

Correlates of Household Seismic Hazard Adjustment Adoption

This study examined the relationships of self-reported adoption of 12 seismic hazard adjustments (pre-impact actions to reduce danger to persons and property) with respondents' demographic characteristics, perceived risk, perceived hazard knowledge, perceived protection responsibility, and perceived attributes of the hazard adjustments. Consistent with theoretical predictions, perceived attributes of the hazard adjustments differentiated among the adjustments and had stronger correlations with adoption than any of the other predictors. These results identify the adjustments and attributes that emergency managers should address to have the greatest impact on improving household adjustment to earthquake hazard.     

Spatial Vulnerability of Network Systems under Spatially Local Hazards

A hazard is often spatially local in a network system, but its impact can spread out through network topology and become global. To qualitatively and quantitatively assess the impact of spatially local hazards on network systems, this article develops a new spatial vulnerability model by taking into account hazard location, area covered by hazard, and impact of hazard (including direct impact and indirect impact), and proposes an absolute spatial vulnerability index (ASVI) and a relative spatial vulnerability index (RSVI). The relationship between the new model and some relevant traditional network properties is also analyzed. A case study on the spatial vulnerability of the Chinese civil aviation network system is conducted to demonstrate the effectiveness of the model, and another case study on the Beijing subway network system to verify its relationship with traditional network properties.     

Hazard Perception, Risk Perception, and the Need for Decontamination by Residents Exposed to Soil Pollution: The Role of Sustainability and the Limits of Expert Knowledge

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments—or the objective risks—can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.     

Team Dispersion,Information Technology,and Project Performance

The impact of information technology (IT) on the performance of distributed projects is not well understood. Although prior research has documented that dispersion among project teams has an adverse effect on project performance, the role of IT as an enabler of communication to bridge the spatial distance among team members in distributed networks has not been empirically studied. We focus on the role of IT as a moderator of the relationship between team dispersion and project performance using projects as the unit of analysis. We find that IT mitigates the negative effect of team dispersion on project performance, especially in high information volume projects. Our central contribution is the development of an empirically tested model to improve the understanding of the operational impact of IT as a vehicle to bridge spatial dispersion among distributed teams that are engaged in knowledge‐intensive work.     

Hazard Characteristics and Patterns of Environmental Injustice: Household‐Level Determinants of Environmental Risk in Miami,Florida

Limited systematic comparative knowledge exists about patterns of environmental injustices in exposure to varied natural and technological hazards. To address this gap, we examine how hazard characteristics (i.e., punctuated event/suddenness of onset, frequency/magnitude, and divisibility) influence relationships between race/ethnicity, nativity, socioeconomic status (SES), older age, housing tenure, and residential hazard exposure. Sociodemographic data come from a random sample survey of 602 residents of the tricounty Miami Metropolitan Statistical Area (Florida). Hazard exposure was measured using spatial data from the Federal Emergency Management Agency, the National Air Toxics Assessment, and the Emergency Response Notification System. We specified generalized estimating equations (GEEs)—which account for sociospatial clustering—predicting 100‐year flood risk, acute chemical accidental releases, and chronic cancer risk from air toxics from all and on‐road mobile sources. We found that for punctuated, sudden onset events, some socially advantaged people were significantly at risk. Racial/ethnic minority variables were significant predictors of greater exposure to the three technological hazards, while higher SES was associated with 100‐year flood risk exposure. Black and foreign‐born Hispanic residents, and white and U.S.‐born Hispanic residents, shared nearly identical risk profiles. Results demonstrate the complexities found in human‐hazard associations and the roles of hazard characteristics in shaping disparate risk patterns.     

油田开发污染源危险度评价模型及实证研究

针对油田开发污染源存在危险度,提出一种将灰关联度分析与故障树分析相结合的危险度评价模型.该模型运用灰关联度分析方法进行事故模式的识别,并根据某一具体的故障树,分析和导出顶事件发生的各种故障模式的可能性大小.然后,选取大庆油田工程有限公司典型案例进行实证研究,结果表明该方法对油田开发污染源危险度评价具备可行性和操作性.     

Resource Allocation in Integrated Preoperational and Operational Management of Natural Hazards

The management of natural hazards occurring over a territory entails two main phases: a preoperational —or pre-event—phase, whose objective is to relocate resources closer to sites characterized by the highest hazard, and an operational —during the event—phase, whose objective is to manage in real time the available resources by allocating them to sites where their intervention is needed. Obviously, the two phases are closely related, and demand a unified and integrated treatment. This work presents a unifying framework that integrates various decisional problems arising in the management of different kinds of natural hazards. The proposed approach, which is based on a mathematical programming formulation, can support the decisionmakers in the optimal resource allocation before (preoperational phase) and during (operational phase) an emergency due to natural hazard events. Different alternatives of modeling the resources and the territory are proposed and discussed according to their appropriateness in the preoperational and operational phases. The proposed approach can be applied to the management of any natural hazard and, from an integration perspective, may be particularly useful for risk management in civil protection operations. An application related to the management of wildfire hazard is presented.     

Probabilistic Integrated Human Mixture Risk Assessment of Multiple Metals Through Seafood Consumption

Inorganic arsenic (iAs), cadmium (Cd), lead (Pb), and methylmercury (MeHg) are toxic metals that cause substantial health concern and are present in various seafood items. This study linked probabilistic risk assessment to the interactive hazard index (HI_INT) approach to assess the human mixture risk posed by the dietary intake of iAs, Cd, Pb, and MeHg from seafood for different age populations, and joint toxic actions and toxic interactions among metals were also considered in the assessment. We found that, in combination, an iAs–Cd–Pb–MeHg mixture synergistically causes neurological toxicity. Furthermore, an iAs–Cd–Pb mixture antagonistically causes renal and hematological effects and additively causes cardiovascular effect. Our results demonstrated that if toxic interactions are not considered, the health risk may be overestimated or underestimated. The 50th percentile HI_INT estimates in all age populations for neurological, renal, cardiovascular, and hematological effects were lower than 1; however, the 97.5th percentile HI_INT estimates might exceed 1. In particular, toddlers and preschoolers had the highest neurological risk, with 0.16 and 0.19 probabilities, respectively, of neurological HI_INT exceeding 1. Saltwater fish consumption was the principal contributor to the health risk. We suggest that regular monitoring of metal levels in seafood, more precise dietary surveys, further toxicological data, and risk–benefit analysis of seafood consumption are warranted to improve the accuracy of human mixture risk assessment and determine optimal consumption.     

Nonparametric Identification of a Contract Model With Adverse Selection and Moral Hazard

This paper studies the nonparametric identification of a contract model with adverse selection and moral hazard. Specifically, we consider the false moral hazard model developed by Laffont and Tirole (1986). We first extend this model to allow for general random demand and cost functions. We establish the nonparametric identification of the demand, cost, deterministic transfer, and effort disutility functions as well as the joint distribution of the random elements of the model, which are the firm's type and the demand, cost, and transfer shocks. The cost of public funds is identified with the help of an instrument. Testable restrictions of the model are characterized.     

Intake fraction for multimedia pollutants: a tool for life cycle analysis and comparative risk assessment.

We employ the intake fraction (iF) as an effective tool for expressing the source-to-intake relationship for pollutant emissions in life cycle analysis (LCA) or comparative risk assessment. Intake fraction is the fraction of chemical mass emitted into the environment that eventually passes into a member of the population through inhalation, ingestion, or dermal exposure. To date, this concept has been primarily applied to pollutants whose primary route of exposure is inhalation. Here we extend the use of iF to multimedia pollutants with multiple exposure pathways. We use a level III multimedia model to calculate iF for TCDD and compare the result to one calculated from measured levels of dioxin toxic equivalents in the environment. We calculate iF for emissions to air and surface water for 308 chemicals. We correlate the primary exposure route with the magnitudes of the octanol-water partition coefficient, Kow, and of the air-water partitioning coefficient (dimensionless Henry constant), Kaw. This results in value ranges of Kow and Kaw where the chemical exposure route can be classified with limited input data requirements as primarily inhalation, primarily ingestion, or multipathway. For the inhalation and ingestion dominant pollutants, we also define empirical relationships based on chemical properties for quantifying the intake fraction. The empirical relationships facilitate rapid evaluation of many chemicals in terms of the intake. By defining a theoretical upper limit for iF in a multimedia environment we find that iF calculations provide insight into the multimedia model algorithms and help identify unusual patterns of exposure and questionable exposure model results.     

Linking inventory efficiency,productivity and responsiveness to retail firm outperformance: empirical insights from US retailing segments

This paper establishes an empirical model linking a retail firm’s inventory management effectiveness to superior competitive operational performance for specific product-line retail segments. Using 16?years of US retail firm financial data from the COMPUSTAT Fundamentals database across 12 distinct competitive retailing segments, we develop and test a time-series model that links several inventory management execution measures to the competitive operational outperformance of retail firms. The analysis presented provides strong evidence that measures of inventory management performance are not ‘one size fits all’ for the retail industry, and helps to explain why extant research has had difficulty linking inventory control policy effectiveness to operational performance advantages in retailing. We discuss the implications of these empirical findings on the study of inventory policy execution, and offer some guidance for further research.