Conscious worst case definition for risk assessment, part II: A methodological case study for pesticide risk assessment

This paper illustrates, by a case study, how to apply the conceptual Worst-Case Definition (WCD) model, developed in the methodological paper in the current journal, by Sørensen et al. (2010-this issue). The case is about eco-toxicological risk assessment of pesticides under Danish conditions. Cumulative aspects are included on a conceptual basis as elements of the worst-case conditions. This defines factors that govern the risk assessment, including location in time and space of risk “hotspots”. Two pillars of concern drive the conceptual modelling: (1) What to protect (denoted Protected Units (PUs)) and (2) the reason for increased risk level (denoted Causes of Risks (CRs)). Both PUs and CRs are analysed using hierarchical procedures that facilitate a complete listing of concrete factors governing increased risk for adverse effect due to agricultural usage of pesticide. The factors governing pesticide risk are combined in a context that combines the protection of relevant groupings of organisms with the factors for increased risk level for each of these. Identification of the most important relations between defined types of PUs and CRs is illustrated using expert knowledge. Existing databases are used to form spatial distributed risk indicators as estimators for a selection of important relations between PUs and CRs. This paper illustrates how the WCD model can break down the complex issue of uncertainty into fractions that are more open for evaluations. Finally, it shows application of risk indicators in a multi-criterion analysis using respectively self organizing mapping and partial order technique in a comparative analysis that highlights critical aspects of uncertainty, due to the ambiguity between single risk indicator rankings.     

基于未确知聚类的高层建筑防火风险评估系统

目前,高层建筑的火灾防控难题一直未得到有效解决。针对高层民用建筑防火能力风险评估中评估指标获取不科学、指标体系差异大的问题,运用典型火灾事件分析法,结合《建筑设计防火规范》,科学获取影响高层建筑防火能力的12个主要不确定性风险因素,构建了更为科学的高层建筑防火能力风险评估指标体系。在此基础上,引入未确知聚类理论,构建了基于未确知聚类的高层建筑防火能力风险评估模型。并以8栋典型高层民用建筑火灾风险数据为例,进行实证分析。研究成果表明,该风险评估系统可行有效。研究成果可为高层民用建筑火灾风险防控提供一种新的方法和途径。     

Environmental risk assessment of industrial facilities: Techniques,regulatory initiatives and insurance

Most companies that manufacture, handle or dispose of chemicals or petroleum products have the potential to cause environmental impairment, especially by longterm or gradual release of materials into the environment. This impairment creates potential liabilities that result from numerous regulations as well as from common law. One way to identify these potential environmental liabilities and exposures is through environmental risk assessment. The primary focus of an environmental risk assessment is to evaluate the potential for off-site gradual impairment arising from a company's operations. Such an assessment reviews the status of the firm's environmental risk exposure and is a useful internal tool for corporate planning. There are three major objectives in performing an environmental risk assessment: risk identification, risk evaluation and risk reduction. To identify risk, numerous criteria are used to determine the individual factors contributing to the potential for off-site exposure. The interaction of these individual risk factors is then used to evaluate the overall potential for gradual environmental impairment. After the risks have been evaluated, recommendations are made to reduce the potential exposures. In addition, implementation of risk reduction strategies accomplish the objective of legislative initiatives for protecting human health and the environment. Environmental risk management can and should be encouraged through legislative initiatives.     

Environmental risk mapping of pollutants: State of the art and communication aspects

Risk maps help risk analysts and scientists to explore the spatial nature of the effects of environmental stressors such as pollutants. The development of Geographic Information Systems over the past few decades has greatly improved spatial representation and analysis of environmental information and data. Maps also constitute a powerful tool to communicate the outcome of complex environmental risk assessment to stakeholders such as the general public and policy makers. With appropriate cartography one can improve communication and thus bridge the gap between experts and users. Appropriate risk communication is pivotal to risk management, decision making and implementation and may prevent unnecessary concern about environmental pollutants. However, at present few risk maps are specifically tailored to meet the demands of such defined uses.This paper presents an overview of the most important types of risk maps that can be distinguished using examples from the scientific literature: contamination maps, exposure maps, hazard maps, vulnerability maps and ‘true’ risk maps. It also discusses, in a general way, the most important issues that need to be addressed when making risk maps for communication purposes: risk perception, target audience, scale and spatial aggregation and visualisation such as use of colours and symbols. Finally, some general rules of thumb are given for making environmental risk maps for communication purposes.     

基于加权贝叶斯网络的森林火灾风险评估

基于森林火灾风险因素的不确定性及应急管理和救援力量介入对森林火灾风险管控的影响,构建森林火灾风险评估指标体系。结合领域专家的经验和知识,基于贝叶斯网络模型,绘制森林火灾风险网络图,对森林火灾发生的不确定性进行明确和处理;基于信息增益计算各指标权重,确定网络图中各指标节点的贡献值,建立加权贝叶斯网络评估模型。对我国内蒙古自治区森林火灾风险开展评估。分析结果表明,该评估模型能够有效对森林火灾的风险进行评估,具有一定的实际应用价值。     

A Bayesian network model to assess the public health risk associated with wet weather sewer overflows discharging into waterways

Overflows from sanitary sewers during wet weather, which occur when the hydraulic capacity of the sewer system is exceeded, are considered a potential threat to the ecological and public health of the waterways which receive these overflows. As a result, water retailers in Australia and internationally commit significant resources to manage and abate sewer overflows. However, whilst some studies have contributed to an increased understanding of the impacts and risks associated with these events, they are relatively few in number and there still is a general lack of knowledge in this area. A Bayesian network model to assess the public health risk associated with wet weather sewer overflows is presented in this paper. The Bayesian network approach is shown to provide significant benefits in the assessment of public health risks associated with wet weather sewer overflows. In particular, the ability for the model to account for the uncertainty inherent in sewer overflow events and subsequent impacts through the use of probabilities is a valuable function. In addition, the paper highlights the benefits of the probabilistic inference function of the Bayesian network in prioritising management options to minimise public health risks associated with sewer overflows.     

The industrial role in risk assessment

Industry has a major role in the assessment and management of risk to society from its operations. Much of the basic knowledge of manufacturing operations, product distribution, use and ultimate disposal of products and byproducts resides in industry. Basic data on the health and environmental effects of materials in commerce has been generated by industry. This information must be utilized in the evaluation of risk so that appropriate management decisions can be made. Experience gained in the industrial sector with risk assessment and management should be of value to government in its oversight role on behalf of society. There is growing realization in both industry and government of the need for more effective communication of risk to the general public in the context of management decisions.     

Conceptual modeling for identification of worst case conditions in environmental risk assessment of nanomaterials using nZVI and C60 as case studies

Conducting environmental risk assessment of engineered nanomaterials has been an extremely challenging endeavor thus far. Moreover, recent findings from the nano-risk scientific community indicate that it is unlikely that many of these challenges will be easily resolved in the near future, especially given the vast variety and complexity of nanomaterials and their applications. As an approach to help optimize environmental risk assessments of nanomaterials, we apply the Worst-Case Definition (WCD) model to identify best estimates for worst-case conditions of environmental risks of two case studies which use engineered nanoparticles, namely nZVI in soil and groundwater remediation and C₆₀ in an engine oil lubricant. Results generated from this analysis may ultimately help prioritize research areas for environmental risk assessments of nZVI and C₆₀ in these applications as well as demonstrate the use of worst-case conditions to optimize future research efforts for other nanomaterials. Through the application of the WCD model, we find that the most probable worst-case conditions for both case studies include i) active uptake mechanisms, ii) accumulation in organisms, iii) ecotoxicological response mechanisms such as reactive oxygen species (ROS) production and cell membrane damage or disruption, iv) surface properties of nZVI and C₆₀, and v) acute exposure tolerance of organisms. Additional estimates of worst-case conditions for C₆₀ also include the physical location of C₆₀ in the environment from surface run-off, cellular exposure routes for heterotrophic organisms, and the presence of light to amplify adverse effects. Based on results of this analysis, we recommend the prioritization of research for the selected applications within the following areas: organism active uptake ability of nZVI and C₆₀ and ecotoxicological response end-points and response mechanisms including ROS production and cell membrane damage, full nanomaterial characterization taking into account detailed information on nanomaterial surface properties, and investigations of dose-response relationships for a variety of organisms.     

Data base for risk assessment

Health risk assessment associated with exposure to toxic chemicals is a process consisting of three basic elements: (i) hazard identification, (ii) risk estimation, and (iii) risk evaluation. Each of these elements provides a data base for making decisions regarding the control of chemical hazards for the prevention of health risk. Each of these elements involves various degrees of uncertainty, yet credibility of the management of risk requires that risk assessment be made with the highest possible accuracy and degree of confidence.     

Chlorination disinfection by-products, public health risk tradeoffs and me

Since 1974 when trihalomethanes (THMs) were first reported as disinfection by-products (DBPs) in drinking water, there has been an enormous research effort directed at understanding how DBPs are formed in the chlorination or chloramination of drinking water, how these chlorination DBPs can be minimized and whether they pose a public health risk, mainly in the form of cancer or adverse reproductive outcomes. Driven by continuing analytical advances, the original DBPs, the THMs, have been expanded to include over 600 DBPs that have now been reported in drinking water. The historical risk assessment context which presumed cancer could be mainly attributed to exposure to environmental carcinogens played a major role in defining regulatory responses to chlorination DBPs which, in turn, strongly influenced the DBP research agenda. There are now more than 30 years of drinking water quality, treatment and health effects research, including more than 60 epidemiology studies on human populations, directed at the chlorination DBP issue. These provide considerable scope to reflect on what we know now, how our understanding has changed, what those changes mean for public health risk management overall and where we should look to better understand and manage this issue in the future.     

Improving the risk quantification under behavioural tendencies: A tale of construction projects

Complex construction projects are risky owing to several features and factors. Their management involves risk assessment which is subjected to various behavioural tendencies and the existing body of knowledge lacks appropriate methods to quantify these effects. The prevalent standard model of Expected Utility Theory does not differentiate between threat and opportunity, resulting into an identical estimation for both facets of risk. This limitation was addressed by Prospect Theory which better captures risk preferences. However, construction industry still relies upon conventional methods of risk assessment. The current study introduces a weighting function to better quantify the cognitive errors in construction risk assessment by adjusting the over- and under-estimation. In doing so, detailed scenario-based, semi-structured interviews are conducted engaging senior professionals. It is found that, typically, opportunities are underestimated by 7.5% and threats are overestimated by 8%. Integrating these findings into risk response strategies results into a realistic and effective resource allocation.     

Role of slope reliability analysis in landslide risk management

Progress in the use of qualitative and quantitative methods of landslide risk assessment is briefly reviewed. The use of a hazard-consequence matrix approach is highlighted and attention is then restricted to aspects of hazard assessment in which formal reliability concepts can be used. Widely accepted geotechnical and geological models must form the basis of credible hazard assessments under different environmental conditions. However, conventional deterministic methods of geotechnical analysis need to be supplemented by studies within a probabilistic framework which takes into consideration parameter variability and other uncertainties. Suggestions are made for using the "reliability index" in preference to the "factor of safety" in comprehensive procedures for landslide risk management. Electronic Publication     

A total environmental risk assessment model for international hub airports

This paper presents a multi-criteria decision analysis for environmental risk assessment (ERA) with regard to avoiding and eliminating damages and loss under natural disasters in international airport projects. It starts from an assumption that the strategy of eliminating damages and losses under natural disasters is related to the location selection problem, and it is necessary to use the multi-criteria decision analysis for calculated decision-making support. The paper uses the analytic network process (ANP) to demonstrate one of its utility modes in decision-making support to location selection problems, which aims at an evaluation of different projects from different locations. A set of generic criteria for risk assessment at international projects was put forward to support ANP modelling, and it was due to the consideration of social, technical, economic, environmental and political (STEEP) criteria related to the built, social and natural (BSN) trinity environment of international airport projects. At the end, an experimental case study on three international hub airports in China is given to test the ANP model called ERA.Airport, and it is concluded that ANP can be effectively used for risk assessment in the specific utility mode. The ERA.Airport is a generic multi-criteria decision-making model and can be used across the world for accurate environmental risk assessment for international airports.     

A fuzzy inference-based approach for building damage risk assessment on mining terrains

Reliable evaluation of risk of building damage due to the mining impact is problematic owing to the magnitude, diversity and uncertainty of factors that may affect the surface, as well as the subjective character of methods of assessing resistance of the objects. The uncertainty and ambiguity elements in the decision process can be accounted for by fuzzy inference method. This tool employed together with GIS enabled one to integrate such diverse factors affecting damage risk as surface deformations and resistance of building objects, taking into account uncertainty of data and subjectivity of evaluation of experts making the assessment.The results of investigations of the damage risk model based on fuzzy inference are presented in the paper. The successive stages of working out a fuzzy model are presented, the most important stages indicated and the choice of specific elements of the model justified. The advantages of fuzzification are presented on the example of building data subjected to the mining impact in one of the Polish mining areas.     

A fuzzy approach to construction project risk assessment

The increasing complexity and dynamism of construction projects have imposed substantial uncertainties and subjectivities in the risk analysis process. Most of the real-world risk analysis problems contain a mixture of quantitative and qualitative data; therefore quantitative risk assessment techniques are inadequate for prioritizing risks. This article presents a risk assessment methodology based on the Fuzzy Sets Theory, which is an effective tool to deal with subjective judgement, and on the Analytic Hierarchy Process (AHP), which is used to structure a large number of risks. The proposed methodology incorporates knowledge and experience acquired from many experts, since they carry out the risks identification and their structuring, and also the subjective judgements of the parameters which are considered to assess the overall risk factor: risk impact, risk probability and risk discrimination. All of these factors are expressed by qualitative scales which are defined by trapezoidal fuzzy numbers to capture the vagueness in the linguistic variables. The most notable differences with other fuzzy risk assessment methods are the use of an algorithm to handle the inconsistencies in the fuzzy preference relation when pair-wise comparison judgements are necessary, and the use of trapezoidal fuzzy numbers until the defuzzification step. An illustrative example on risk assessment of a rehabilitation project of a building is used to demonstrate the proposed methodology.     

Response to Mugdan et al.'s comment on Urban et al. “Assessment of human health risks posed by consumption of fish from the Lower Passaic River (LPR), New Jersey” (2009, doi:10.1016/jscitotenv.2009.03.004)

Mugdan et al. have criticized certain aspects of the approach and general conclusions of our recently published fish ingestion risk assessment for the lower Passaic River (Urban et al., 2009), asserting that they are inconsistent with the United States Environmental Protection Agency's risk assessment guidelines we reference in our paper. Specifically, they assert that the excess cancer risk and health hazard results calculated as a part of our analyses underestimate the potential health risk posed to lower Passaic River anglers who actually consume their catch due to the fish ingestion rates we utilized in our analysis and our lack of inclusion of a crab ingestion pathway. While there clearly are differences between our risk assessment and the one conducted by the USEPA, this is not at all surprising given that their assessment reflects a typical screening-level risk assessment while that described in our paper reflects a more detailed site-specific risk assessment. In developing our exposure scenarios and assumptions, we considered and incorporated the available site-specific information in both deterministic and probabilistic quantitative risk frameworks in an effort to provide a sound and realistic human health risk assessment that quantitatively accounts for much of the variability and uncertainty typically inherent in such estimates. Although it is understandable that Mugdan et al. are compelled to defend the effort and conclusions put forth by USEPA Region 2 in its 2007 draft human health risk assessment of the lower Passaic River, the site-specific lower Passaic River human health risk assessment presented in Urban et al. (2009) was conducted according to USEPA guidelines, underwent peer review, and is, in fact, consistent with Superfund guidance and accepted principles of risk assessment.     

A GIS-based human health risk assessment for urban green space planning—An example from Grugliasco (Italy)

The need to develop approaches for risk-based management of soil contamination, as well as the integration of the assessment of the human health risk (HHR) due to the soil contamination in the urban planning procedures has been the subject of recent attention of scientific literature and policy makers. The spatial analysis of environmental data offers multiple advantages for studying soil contamination and HHR assessment, facilitating the decision making process. The aim of this study was to explore the possibilities and benefits of spatial implementation of a quantitative HHR assessment methodology for a planning case in a typical urban environment where the soil is contaminated. The study area is located in the city of Grugliasco a part of the Turin (Italy) metropolitan area.The soils data were derived from a site specific soil survey and the land-use data from secondary sources. In the first step the soil contamination data were geo-statistically analysed and a spatial soil contamination data risk modelling procedure designed. In order to spatially assess the HHR computer routines were developed using GIS raster tools. The risk was evaluated for several different land uses for the planned naturalistic park area.The HHR assessment indicated that the contamination of soils with heavy metals in the area is not sufficient to induce considerable health problems due to typical human behaviour within the variety of urban land uses. An exception is the possibility of direct ingestion of contaminated soil which commonly occurs in playgrounds.The HHR evaluation in a planning case in the Grugliasco Municipality confirms the suitability of the selected planning option. The construction of the naturalistic park presents one solution for reducing the impacts of soil contamination on the health of citizens. The spatial HHR evaluation using GIS techniques is a diagnostic procedure for assessing the impacts of urban soil contamination, with which one can verify planning options, and provides an important step in the integration of human health protection within urban planning procedures.     

Assessing the impact of waterborne and dietborne cadmium toxicity on susceptibility risk for rainbow trout

The purpose of this study was to use a risk-based integrated-scale toxicological model to examine the impact of waterborne and dietborne cadmium (Cd) toxicity on rainbow trout (Oncorhynchus mykiss) susceptibility appraised with recent published data. A probabilistic assessment model was performed to estimate Cd susceptibility risk. The dose-response models were constructed based on two endpoints of % Cd in metabolically active pool (MAP) and susceptibility time that causes 50% effect (ST50). We further constructed an elimination-detoxification-recovery scheme to enhance the model predictive ability. We found a 95% probability of % Cd in gill and liver MAP exceeding 47-49% and it was likely (70% probability) to have exceeded 52-55%, but it was unlikely (30% probability) to have exceeded 56-60%. In contrast to gill and liver, gut had a relative lower Cd susceptibility risk (15-17% Cd in MAP) with a longer ST50. We suggested that the proposed probabilistic risk assessment framework can incorporate the elimination-detoxification-recovery scheme to help government based biomonitoring and bioassessment programs to prevent potential aquatic ecosystems and human health consequences.     

Assessment of the value of reducing uncertainty by sampling in a groundwater remediation system

The success of cleaning up a contaminated site depends on the degree of knowledge of the site's characteristics. When there is much uncertainty associated with the knowledge, the uncertainty regarding whether the remediation will work increases consequently. It is therefore essential to know how much reduction of uncertainty is needed for the purpose of designing a successful and reliable remediation system. The understanding of the site characteristics is basically increased by site investigation, and thus the uncertainty is decreased by sampling information. This study develops a method to evaluate the value of reducing uncertainty by sampling the hydrogeological parameters in a groundwater remediation system. Hydraulic conductivity being taken as an example of the site characteristics, random field generation and conditional simulation are coupled to obtain a range of hydraulic conductivity fields based on the sampling outputs. A multiple-realization management model that incorporates a chance constraint of health risk is used to find the lowest remediation cost under specific remediation criteria of risk through genetic algorithm. The remediation cost, which is expected to decrease with collection of more samples, serves as the measure of the value of uncertainty reduction by sampling. A case study shows that the variation of the hydraulic conductivity fields among the potential sites as well as the remediation cost is reduced as a result of increase of samples. It also shows that the risk after remediation decreases with the collection of more samples, which implies that the reduction of risk can also be used to assess the value of sampling.