Recent developments in the application of risk analysis to waste technologies

The European waste sector is undergoing a period of unprecedented change driven by business consolidation, new legislation and heightened public and government scrutiny. One feature is the transition of the sector towards a process industry with increased pre-treatment of wastes prior to the disposal of residues and the co-location of technologies at single sites, often also for resource recovery and residuals management. Waste technologies such as in-vessel composting, the thermal treatment of clinical waste, the stabilisation of hazardous wastes, biomass gasification, sludge combustion and the use of wastes as fuel, present operators and regulators with new challenges as to their safe and environmentally responsible operation. A second feature of recent change is an increased regulatory emphasis on public and ecosystem health and the need for assessments of risk to and from waste installations. Public confidence in waste management, secured in part through enforcement of the planning and permitting regimes and sound operational performance, is central to establishing the infrastructure of new waste technologies. Well-informed risk management plays a critical role. We discuss recent developments in risk analysis within the sector and the future needs of risk analysis that are required to respond to the new waste and resource management agenda.     

Risks posed by climate change to the delivery of Water Framework Directive objectives in the UK

The EU Water Framework Directive (WFD) is novel because it integrates water quality, water resources, physical habitat and, to some extent, flooding for all surface and groundwaters and takes forward river basin management. However, the WFD does not explicitly mention risks posed by climate change to the achievement of its environmental objectives. This is despite the fact that the time scale for the implementation process and achieving particular objectives extends into the 2020s, when climate models project changes in average temperature and precipitation. This paper begins by reviewing the latest UK climate change scenarios and the wider policy and science context of the WFD. We then examine the potential risks of climate change to key phases of the River Basin Management Process that underpin the WFD (such as characterisation of river basins and their water bodies, risk assessments to identify pressures and impacts, programmes of measures (POMs) options appraisal, monitoring and modelling, policy and management activities). Despite these risks the WFD could link new policy and participative mechanisms (being established for the River Basin Management Plans) to the emerging framework of national and regional climate change adaptation policy. The risks are identified with a view to informing policy opportunities, objective setting, adaptation strategies and the research agenda. Key knowledge gaps have already been identified during the implementation of the WFD, such as the links between hydromorphology and ecosystem status, but the overarching importance of linking climate change to these considerations needs to be highlighted. The next generation of (probabilistic) climate change scenarios will present new opportunities and challenges for risk analysis and policy-making.     

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers

Introduction: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. Method: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ‘‘middle-aged and elderly drivers with low risk of driving violations and high historical crash records,” ‘‘drivers with high risk of driving violations and high historical crash records,” and ‘‘middle-aged drivers with no driving violations and conviction records.” Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.     

Predicting the frequency of accidents in port areas by developing event trees from historical analysis

The historical analysis of 828 accidents in port areas, which have been selected from a database, has been used to identify the sequences of the accidents. Processing these data has allowed the event trees and the probability of the various accident scenarios to be determined. By using these event trees and figures detailing the frequency of the events that initiated the accidents, as taken from various authors, the frequency of the accidents has been determined.     

On the critique of Beck’s view on risk and risk analysis

Ulrich Beck’s stand on risk and risk analysis has been challenged by many researchers. In this paper we look closer into some of the arguments used, with a main focus on the fundamental analysis carried out by Campbell and Currie. These two authors argue that Beck’s criticisms of the theory and practice of risk analysis are groundless: Beck’s understanding of what risk is, is badly flawed, and he misunderstands and distorts the use of probability in risk analysis. However, the analysis of Campbell and Currie is based on a set of premises, for example that risk is a function of probability and harm, and that risk really exists and one can be wrong about risk. Although such ideas are common, they can be challenged, and in the literature a number of alternative perspectives have been suggested. The purpose of the present paper is to study Beck’s stand on risk analysis and the related critique of Campbell and Currie and others, in view of some of these alternative perspectives on risk. To what extent is the critique then justified? The paper concludes that the case raised against Beck’s view is still strong and relevant, but has to be nuanced with respect to some important issues, for example concerning the distinction between belief and truth when it comes to risk. Allowing for spacious interpretations of some of Beck’s theses, the paper provides strengthened support for Beck’s view on these points.     

液体火箭共底破裂爆炸安全设防距离

针对航天发射场一旦发生低温推进剂泄漏而导致火箭爆炸,会对人员和财产造成重大损失的问题,采用TNT当量模型和TNO(The Netherlands Organization)多能模型计算不同摩尔百分比的氢氧推进剂混合反应时产生爆炸冲击波的危害性,并模拟爆炸冲击波造成的事故影响范围,然后对两种模型的仿真结果加以对比分析,根据最不利原则选取出最终需要的结果,最后划分出安全设防距离。由仿真结果可知,不同的氢氧混合摩尔百分比造成的爆炸后果不同,同时TNT当量模型在爆炸近场处高估了爆炸超压值,在爆炸远场处低估了爆炸超压值,而TNO多能模型在理论上有效地对这一缺陷进行了弥补。对航天发射场的安全布局起到了一定的参考价值。     

Uncertainties in QRA: Analysis of losses of containment from piping and implications on risk prevention and mitigation

Quantitative Risk Assessment (QRA) is commonly used in the chemical industry to support decision-making. Common practices are based on standard methods, such as fault tree, event tree, etc.; in this frame, risk is a function of frequency of events (probability) and associated consequences (negative outcomes), but relevant uncertainties often are not properly taken into account in the derived results. This paper presents the application of an extended risk analysis of loss of containments for a case-study with the following aims: firstly, the uncertainties related to the results of the analysis, which derive from assumption in the application of the standard models, are qualitatively assessed; secondly the application allows evaluating the impact of the uncertainties on the trustworthiness of the results and, finally, commenting about their use in the risk prevention and mitigation.     

Multi-criteria decision-making considering risk and uncertainty in physical asset management

In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.     

How can process safety and a risk management approach guide pandemic risk management?

The coronavirus disease (COVID-19) brought the world to a halt in March 2020. Various prediction and risk management approaches are being explored worldwide for decision making. This work adopts an advanced mechanistic model and utilizes tools for process safety to propose a framework for risk management for the current pandemic. A parameter tweaking and an artificial neural network-based parameter learning model have been developed for effective forecasting of the dynamic risk. Monte Carlo simulation was used to capture the randomness of the model parameters. A comparative analysis of the proposed methodologies has been carried out by using the susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD) model. A SEIQRD model was developed for four distinct locations: Italy, Germany, Ontario, and British Columbia. The learning-based approach resulted in better outcomes among the models tested in the present study. The layer of protection analysis is a useful framework to analyze the effect of different safety measures. This framework is used in this work to study the effect of non-pharmaceutical interventions on pandemic risk. The risk profiles suggest that a stage-wise releasing scenario is the most suitable approach with negligible resurgence. The case study provides valuable insights to practitioners in both the health sector and the process industries to implement advanced strategies for risk assessment and management. Both sectors can benefit from each other by using the mathematical models and the management tools used in each, and, more importantly, the lessons learned from crises.