Application of the operating window concept to remediation‐option selection

An Erratum has been published for this article in Remediation 14(4) 2004, 141. The selection of remediation options for the management of unacceptable risks at contaminated sites is hindered by insufficient information on their performance under different site conditions. Therefore, there is a need to define “operating windows” for individual remediation options to summarize their performance under a variety of site conditions. The concept of the “operating window” has been applied as both a performance optimization tool and decision support tool in a number of different industries. Remediation‐option operating windows could be used as decision support tools during the “options appraisal” stage of the Model Procedures (CLR 11), proposed by the Environment Agency (EA) for England and Wales, to enhance the identification of “feasible remediation options” for “relevant pollutant linkages.” The development of remediation‐option operating windows involves: 1) the determination of relationships between site conditions (“critical variables”) and option performance parameters (e.g., contaminant degradation or removal rates) and 2) the identification of upper‐ and lower‐limit values (“operational limits”) for these variables that define the ranges of site conditions over which option performance is likely to be sufficient (the “operating window”) and insufficient (the “operating wall”) for managing risk. Some research has used case study data to determine relationships between critical variables and subsurface natural attenuation (NA) process rates. Despite the various challenges associated with the approach, these studies suggest that available case study data can be used to develop operating windows for monitored natural attenuation (MNA) and, indeed, other remediation options. It is envisaged that the development of remediation‐option operating windows will encourage the application of more innovative remediation options as opposed to excavation and disposal to landfill and/or on‐site containment, which remain the most commonly employed options in many countries. © 2004 Wiley Periodicals, Inc.     

Rapid manganese removal from mine waters using an aerated packed-bed bioreactor

In the UK, the Environmental Quality Standard for manganese has recently been lowered to 30 microg/L (annual average), which is less than the UK Drinking Water Inspectorate's Maximum Permitted Concentration Value (50 microg/L). Current passive treatment systems for manganese removal operate as open-air gravel-bed filters, designed to maximize either influent light and/or dissolved oxygen. This requires large areas of land. A novel enhanced bioremediation treatment system for manganese removal has been developed that consists of a passively aerated subsurface gravel bed. The provision of air at depth and the use of catalytic substrates help overcome the slow kinetics usually associated with manganese oxidation. With a residence time of only 8 h and an influent manganese concentration of approximately 20 mg/L, >95% of the manganese was removed. The treatment system also operates successfully at temperatures as low as 4 degrees C and in total darkness. These observations have positive implications for manganese treatment using this technique in both colder climates and where large areas of land are unavailable. Furthermore, as the operation of this passive treatment system continually generates fresh manganese oxyhydroxide, which is a powerful sorbent for most pollutant metals, it potentially has major ancillary benefits as a removal process for other metals, such as zinc.     

Science in the public process of ecosystem management: lessons from Hawaii, Southeast Asia, Africa and the US Mainland

Partnerships and co-operative environmental management are increasing worldwide as is the call for scientific input in the public process of ecosystem management. In Hawaii, private landowners, non-governmental organizations, and state and federal agencies have formed watershed partnerships to conserve and better manage upland forested watersheds. In this paper, findings of an international workshop convened in Hawaii to explore the strengths of approaches used to assess stakeholder values of environmental resources and foster consensus in the public process of ecosystem management are presented. Authors draw upon field experience in projects throughout Hawaii, Southeast Asia, Africa and the US mainland to derive a set of lessons learned that can be applied to Hawaiian and other watershed partnerships in an effort to promote consensus and sustainable ecosystem management. Interdisciplinary science-based models can serve as effective tools to identify areas of potential consensus in the process of ecosystem management. Effective integration of scientific input in co-operative ecosystem management depends on the role of science, the stakeholders and decision-makers involved, and the common language utilized to compare tradeoffs. Trust is essential to consensus building and the integration of scientific input must be transparent and inclusive of public feedback. Consideration of all relevant stakeholders and the actual benefits and costs of management activities to each stakeholder is essential. Perceptions and intuitive responses of people can be as influential as analytical processes in decision-making and must be addressed. Deliberative, dynamic and iterative decision-making processes all influence the level of stakeholder achievement of consensus. In Hawaii, application of lessons learned can promote more informed and democratic decision processes, quality scientific analysis that is relevant, and legitimacy and public acceptance of ecosystem management.     

Cultural and individual differences in self‐rating behavior: an extension and refinement of the cultural relativity hypothesis

This study examined the relationships between culture, individual attributes, and self‐rating behavior among 1,786 university students in Canada, Hong Kong, Taiwan, mainland China, and Japan, and in doing so extended and refined the cultural relativity hypothesis. It explored the difference between vertical and horizontal individualists in self‐rating behavior, and examined the mediating effects of two individual attributes, self‐enhancement propensity and general self‐efficacy in the relationship between individualism and self‐rating behavior. The results confirmed that individualism is the cultural driver for self‐rating leniency, and that the individual‐level assessment of individualism is a stronger predictor of self‐rating leniency than are culture‐level differences. Vertical individualism was found to be positively related to self‐enhancement propensity, which in turn was positively related to self‐rating. Whereas, horizontal individualism was positively related to general self‐efficacy, which in turn had a positive relationship with self‐rating. We discuss the implications of the results for academic research and practical management. Copyright © 2006 John Wiley & Sons, Ltd.     

The estimated reduction in the odds of loss-of-control type crashes for sport utility vehicles equipped with electronic stability control

INTRODUCTION: Using data from the NASS General Estimates System (GES), the method of induced exposure was used to assess the effects of electronic stability control (ESC) on loss-of-control type crashes for sport utility vehicles. METHOD: Sport utility vehicles were classified into crash types generally associated with loss of control and crash types most likely not associated with loss of control. Vehicles were then compared as to whether ESC technology was present or absent in the vehicles. A generalized additive model was fit to assess the effects of ESC, driver age, and driver gender on the odds of loss of control. In addition, the effects of ESC on roads that were not dry were compared to effects on roads that were dry. RESULTS: Overall, the estimated percentage reduction in the odds of a loss-of-control crash for sport utility vehicles equipped with ESC was 70.3%. Both genders and all age groups showed reduced odds of loss-of-control crashes, but there was no significant difference between males and females. With respect to driver age, the maximum percentage reduction of 73.6% occurred at age 27. The positive effects of ESC on roads that were not dry were significantly greater than on roads that were dry.     

A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

An optimal level of dust explosion risk management: Framework and application

The current research provides guidance on the prevention and mitigation of dust explosion using a Quantitative Risk Management Framework (QRMF). Using concepts drawn from previous studies, the framework consists of three main steps: (i) a new combined safety management protocol, (ii) the use of DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to assess explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety). QRMF assessment of an industrial case study showed that the original process was at high risk. DESC simulations and Probit equations determined the destructive percentages. FTAs revealed high probabilities of explosion occurrence; in addition, detailed individual and societal risks calculations were made, before and after the framework was applied. Based on the hierarchy of controls technique, the framework showed significant risk reduction to the point where the residual risk was acceptable for the process.     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.