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.     

On the search for mimetic patterns in environmental disclosure: an international perspective

In this paper, we assert and test the proposition that environmental disclosure (ED) is structured by institutionalised myths and that is why ED is decoupled from environmental performance and media pressures. Focusing on firms from Canada, France and Germany, findings show that ED mimetic isomorphism for different topics varies among countries and by industry sensitiveness to the environment. The results corroborate the institutional presumption that institutionalised myths vary among different contexts. Our findings also suggest that institutionalised ED structures may not reflect environmental performance, mimetic patterns being affected by environmental performance. However, the decoupling between ED mimetic isomorphism and environmental performance decrease when firms’ ED credibility is questioned by the media.     

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.     

Optimization of facility location and reallocation in an industrial plant through a multi-annual framework accounting for economic and safety issues

The industrial layout traditionally has been addressed accounting for the facilities distribution and installation since the first day of operation of the plant; this is, without considering future expansions that involve additional facilities in the future operation years. This way, this paper proposes a mathematical programming formulation for the optimal facility sitting and reallocation in an industry accounting for future expansions and involving simultaneously economic and safety objectives. The proposed formulation is based on a multi-annual framework and this corresponds to a multi-objective mixed integer linear programming problem. The proposed optimization approach was applied to a case study for the facility sitting (office buildings and control rooms) in an ethylene oxide plant. The economic objective function involves the minimization of the total annual cost accounting for the value of the money through the time and the safety objective function involves the minimization for the accumulated risk over the operation time. Results show the applicability of the proposed approach.     

Alcohol is a predictor of mortality in motor vehicle collisions

IntroductionIt is well recognized that driving while intoxicated increases the probability of a motor-vehicle collision (MVC). The effect of alcohol on the chance of surviving the MVC is less clear. Method: Using data from the Fatality Analysis Reporting System (FARS) we conducted analyses for the outcome of mortality using alcohol and other variables as predictors. We also selected alcohol positive (AP) and alcohol negative (AN) persons from the same MVC and vehicle to control for confounding characteristics. Results: The odds ratio (OR) for mortality for alcohol positive drivers was 2.57, (p < 0.001 for all the following OR). Other harmful predictive factors were age OR 1.01 per year, vehicle age OR 1.05 per year, male sex OR 1.23, avoidance maneuver OR 1.09, speed related OR 2.89, rollover mechanism OR 2.75, and collision with a fixed object OR 6.70. Protective factors were proper restraint use – OR 0.19 and collision with another moving vehicle, OR 0.21. In the multivariate analysis the OR of mortality for AP vs AN was 1.46. Proper restraint use (OR 0.27) remained protective along with collision with another moving vehicle. When AP and AN persons from the same MVC and the same vehicle were compared, the adjusted OR’s for mortality were 1.46 and 2.08, respectively. Conclusions: Alcohol is an independent predictor of mortality in an MVC. Proper restraint use is the strongest protective factor. This finding allows a more complete understanding of the risks of driving while intoxicated, not only a higher probability of an MVC, but decreased survival once the MVC occurs. Practical Applications: Identification of alcohol as an independent predictor of mortality in an accident may improve risk assessment and influence drivers to avoid driving while intoxicated.     

Extrinsic and intrinsic determinants of winter foraging and breeding phenology in a temperate seabird

In temperate regions, winter presents animals with a number of challenges including depressed food abundance, increased daily energy requirements, higher frequency of extreme weather events and shortened day length. Overcoming these constraints is critical for overwintering survival and scheduling of future breeding of long-lived species and is likely to be state dependent, associated with intrinsic abilities such as food acquisition rates. We examined the relationship between environmental and intrinsic factors on overwintering foraging and subsequent breeding phenology of the European shag Phalacrocorax aristotelis, a diurnal marine predator. We tested a range of hypotheses relating to overwintering foraging time and location. We found that individuals greatly increased their foraging time in winter to a peak of more than 90% of available daylight at the winter solstice. The seasonal patterns of foraging time appear to be driven by a combination of light levels and weather conditions and may be linked to the availability of the shag's principal prey, the lesser sandeel Ammodytes marinus. There was no evidence that shags dispersed south in winter to increase potential foraging time. Foraging time decreased after the winter solstice and, crucially, was correlated with subsequent breeding phenology, such that individuals that spent less time foraging in February bred earlier. The relationship was much stronger in females than males, in line with their more direct control of timing of breeding. Our results demonstrate that pre-breeding intrinsic foraging ability is critical in determining breeding phenology.     

Strategic environmental policy; eco-dumping or a green strategy?

The Porter hypothesis claims that a strong environmental policy best serves the interests of a nation's export industry. While this hypothesis seems to be based on some form of bounded rationality, this paper argues that governments may have good reasons for setting an especially strong environmental policy even though firms are fully rational. If the available abatement technology turns the environment into an “inferior input”, competitiveness is spurred by a strong environmental policy. The government should take advantage of this, and set an especially strict emission quota or an especially high emission tax. The findings in the paper also has consequences for the desirability of international cooperation with respect to national environmental policy. If a strict environmental policy spurs competitiveness, the environment is better protected without cooperation.     

Influence of maternal food availability on offspring dispersal

Prenatal effects caused by the maternal environment during gestation are known to contribute to the phenotype of the offspring. Whether they have some adaptive value is currently under debate. We experimentally tested the existence of such a maternal effect (food availability during gestation) on dispersal of offspring in the common lizard (Lacerta vivipara). Pregnant females were captured and kept in the laboratory until parturition. During this period, females were offered two rates of food delivery. After parturition, we released mothers and offspring at the mother's capture point. Dispersal of young was significantly affected by the mother's nutrition. To our knowledge, this is the first evidence of a prenatal effect on dispersal. Offspring of well fed mothers dispersed at a higher rate than those of less well fed mothers. As current hypotheses clearly predict the opposite result, our evidence calls for their reassessment. Dispersers are not always the least fit individuals or those coming from the poorest environments.     

High serum S-equol content in red clover fed ewes: the classical endocrine disruptor is a single enantiomer

An expedient high performance liquid chromatography (HPLC) method was developed for the quantitative analysis of environmental estrogenic isoflavonoids, particularly (S)-equol, in red clover fed ewes. We report here the phytoestrogen analysis of red clover silage and the serum of ewes fed with this feed. Ewes received daily 10.5 g of formononetin on average from red clover silage. In the serum samples a major part of formononetin had been metabolised to equol (average 7.7 μg ml⁻¹). According to chiral HPLC analysis, the equol present in the serum of ewes was solely of the (S)-form. We also demonstrate the presence of the metabolite O-demethylangolensin (O-DMA) in ovine serum.     

Elk decision-making rules are simplified in the presence of wolves

The risk of predation drives many behavioral responses in prey. However, few studies have directly tested whether predation risk alters the way other variables influence prey behavior. Here we use information theory (Akaike’s Information Criterion, AICc) in a novel way to test the hypothesis that the decision-making rules governing elk behavior are simplified by the presence of wolves. With elk habitat use as the dependent variable, we test whether the number of independent variables (i.e., the size of the models) that best predict this behavior differ when wolves are present vs absent. Thus, we use AICc scores simply to determine the number of variables to which elk respond when making decisions. We measured habitat use using 2,288 locations from GPS collars on 14 elk, over two winters (14 elk winters), in the Gallatin Canyon portion of the Greater Yellowstone Ecosystem. We found that the use of three major habitat components (grass, conifer, sage) was sensitive to many variables on days that wolves were locally absent, with the best models (ΔAICc≤2) averaging 7.4 parameters. In contrast, habitat use was sensitive to few variables on days when wolves were present: the best models averaged only 2.5 parameters. Because fewer variables affect elk behavior in the presence of wolves, we conclude that elk use simpler decision-making rules in the presence of wolves. This simplification of decision-making rules implies that predation risk imposes selection pressures that do not allow prey to respond to other pressures in ways that they otherwise would. If the affected processes are important, then this indirect effect of predation is likely to be important.