Risk Assessment and Alternatives Assessment: Comparing Two Methodologies

The selection and use of chemicals and materials with less hazardous profiles reflects a paradigm shift from reliance on risk minimization through exposure controls to hazard avoidance. This article introduces risk assessment and alternatives assessment frameworks in order to clarify a misconception that alternatives assessment is a less effective tool to guide decision making, discusses factors promoting the use of each framework, and also identifies how and when application of each framework is most effective. As part of an assessor's decision process to select one framework over the other, it is critical to recognize that each framework is intended to perform different functions. Although the two frameworks share a number of similarities (such as identifying hazards and assessing exposure), an alternatives assessment provides a more realistic framework with which to select environmentally preferable chemicals because of its primary reliance on assessing hazards and secondary reliance on exposure assessment. Relevant to other life cycle impacts, the hazard of a chemical is inherent, and although it may be possible to minimize exposure (and subsequently reduce risk), it is challenging to assess such exposures through a chemical's life cycle. Through increased use of alternatives assessments at the initial stage of material or product design, there will be less reliance on post facto risk‐based assessment techniques because the potential for harm is significantly reduced, if not avoided, negating the need for assessing risk in the first place.     

Biogeographical Analysis of Chemical Co‐Occurrence Data to Identify Priorities for Mixtures Research

A challenge with multiple chemical risk assessment is the need to consider the joint behavior of chemicals in mixtures. To address this need, pharmacologists and toxicologists have developed methods over the years to evaluate and test chemical interaction. In practice, however, testing of chemical interaction more often comprises ad hoc binary combinations and rarely examines higher order combinations. One explanation for this practice is the belief that there are simply too many possible combinations of chemicals to consider. Indeed, under stochastic conditions the possible number of chemical combinations scales geometrically as the pool of chemicals increases. However, the occurrence of chemicals in the environment is determined by factors, economic in part, which favor some chemicals over others. We investigate methods from the field of biogeography, originally developed to study avian species co‐occurrence patterns, and adapt these approaches to examine chemical co‐occurrence. These methods were applied to a national survey of pesticide residues in 168 child care centers from across the country. Our findings show that pesticide co‐occurrence in the child care center was not random but highly structured, leading to the co‐occurrence of specific pesticide combinations. Thus, ecological studies of species co‐occurrence parallel the issue of chemical co‐occurrence at specific locations. Both are driven by processes that introduce structure in the pattern of co‐occurrence. We conclude that the biogeographical tools used to determine when this structure occurs in ecological studies are relevant to evaluations of pesticide mixtures for exposure and risk assessment.     

The Architecture of Chemical Alternatives Assessment

Chemical alternatives assessment is a method rapidly developing for use by businesses, governments, and nongovernment organizations seeking to substitute chemicals of concern in production processes and products. Chemical alternatives assessment is defined as a process for identifying, comparing, and selecting safer alternatives to chemicals of concern (including those in materials, processes, or technologies) on the basis of their hazards, performance, and economic viability. The process is intended to provide guidance for assuring that chemicals of concern are replaced with safer alternatives that are not likely to be later regretted. Conceptually, the assessment methods are developed from a set of three foundational pillars and five common principles. Based on a number of emerging alternatives assessment initiatives, in this commentary, we outline a chemical alternatives assessment blueprint structured around three broad steps: Scope, Assessment, and Selection and Implementation. Specific tasks and tools are identified for each of these three steps. While it is recognized that on‐going practice will further refine and develop the method and tools, it is important that the structure of the assessment process remain flexible, adaptive, and focused on the substitution of chemicals of concern with safer alternatives.     

A Look at State‐Level Risk Assessment in the United States: Making Decisions in the Absence of Federal Risk Values

State environmental agencies in the United States are charged with making risk management decisions that protect public health and the environment while managing limited technical, financial, and human resources. Meanwhile, the federal risk assessment community that provides risk assessment guidance to state agencies is challenged by the rapid growth of the global chemical inventory. When chemical toxicity profiles are unavailable on the U.S. Environmental Protection Agency's Integrated Risk Information System or other federal resources, each state agency must act independently to identify and select appropriate chemical risk values for application in human health risk assessment. This practice can lead to broad interstate variation in the toxicity values selected for any one chemical. Within this context, this article describes the decision‐making process and resources used by the federal government and individual U.S. states. The risk management of trichloroethylene (TCE) in the United States is presented as a case study to demonstrate the need for a collaborative approach among U.S. states toward identification and selection of chemical risk values while awaiting federal risk values to be set. The regulatory experience with TCE is contrasted with collaborative risk science models, such as the European Union's efforts in risk assessment harmonization. Finally, we introduce State Environmental Agency Risk Collaboration for Harmonization, a free online interactive tool designed to help to create a collaborative network among state agencies to provide a vehicle for efficiently sharing information and resources, and for the advancement of harmonization in risk values used among U.S. states when federal guidance is unavailable.     

Spatial Risk Assessment Across Large Landscapes with Varied Land Use: Lessons from a Conservation Assessment of Military Lands

Spatial decision-support tools are necessary for assessment and management of threats to biodiversity, which in turn is necessary for biodiversity conservation. In conjunction with the U.S. Geological Survey-Biological Resources Division's Species at Risk program, we developed a GIS-based spatial decision-support tool for relative risk assessments of threats to biodiversity on the U.S. Army's White Sands Missile Range and Fort Bliss (New Mexico and Texas) due to land uses associated with military missions of the two bases. The project tested use of spatial habitat models, land-use scenarios, and species-specific impacts to produce an assessment of relative risks for use in conservation planning on the 1.2 million-hectare study region. Our procedure allows spatially explicit analyses of risks to multiple species from multiple sources by identifying a set of hazards faced by all species of interest, identifying a set of feasible management alternatives, assigning scores to each species for each hazard, and mapping the distribution of these hazard scores across the region of interest for each combination of species/management alternatives. We illustrate the procedure with examples. We demonstrate that our risk-based approach to conservation planning can provide resource managers with a useful tool for spatial assessment of threats to species of concern.     

Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs)

Adverse outcome pathway Bayesian networks (AOPBNs) are a promising avenue for developing predictive toxicology and risk assessment tools based on adverse outcome pathways (AOPs). Here, we describe a process for developing AOPBNs. AOPBNs use causal networks and Bayesian statistics to integrate evidence across key events. In this article, we use our AOPBN to predict the occurrence of steatosis under different chemical exposures. Since it is an expert-driven model, we use external data (i.e., data not used for modeling) from the literature to validate predictions of the AOPBN model. The AOPBN accurately predicts steatosis for the chemicals from our external data. In addition, we demonstrate how end users can utilize the model to simulate the confidence (based on posterior probability) associated with predicting steatosis. We demonstrate how the network topology impacts predictions across the AOPBN, and how the AOPBN helps us identify the most informative key events that should be monitored for predicting steatosis. We close with a discussion of how the model can be used to predict potential effects of mixtures and how to model susceptible populations (e.g., where a mutation or stressor may change the conditional probability tables in the AOPBN). Using this approach for developing expert AOPBNs will facilitate the prediction of chemical toxicity, facilitate the identification of assay batteries, and greatly improve chemical hazard screening strategies.     

A general guideline for management of risk from carcinogens

A simple relationship is formulated that helps to discriminate between acceptable and unacceptable individual lifetime risks (RL) to populations that are exposed to chemical carcinogens. The relationship is an empirical one and is developed using objective risk data as well as subjective risk levels that have found substantial acceptance among those concerned with carcinogenic risk assessment issues. The expression sets acceptable levels of lifetime carcinogenic risk and is a function of the total population exposed to the carcinogen. Its use in risk assessment and risk management provides guidance in distinguishing those carcinogens that should be regulated because of the health hazard they pose from those whose regulation may not be needed.     

Advances on a Decision Analytic Approach to Exposure-Based Chemical Prioritization

The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high-throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high-level chemical prioritization tool for risk-based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics.     

Cost‐Benefit Analysis for Optimization of Risk Protection Under Budget Constraints

Cost‐benefit analysis (CBA) is commonly applied as a tool for deciding on risk protection. With CBA, one can identify risk mitigation strategies that lead to an optimal tradeoff between the costs of the mitigation measures and the achieved risk reduction. In practical applications of CBA, the strategies are typically evaluated through efficiency indicators such as the benefit‐cost ratio (BCR) and the marginal cost (MC) criterion. In many of these applications, the BCR is not consistently defined, which, as we demonstrate in this article, can lead to the identification of suboptimal solutions. This is of particular relevance when the overall budget for risk reduction measures is limited and an optimal allocation of resources among different subsystems is necessary. We show that this problem can be formulated as a hierarchical decision problem, where the general rules and decisions on the available budget are made at a central level (e.g., central government agency, top management), whereas the decisions on the specific measures are made at the subsystem level (e.g., local communities, company division). It is shown that the MC criterion provides optimal solutions in such hierarchical optimization. Since most practical applications only include a discrete set of possible risk protection measures, the MC criterion is extended to this situation. The findings are illustrated through a hypothetical numerical example. This study was prepared as part of our work on the optimal management of natural hazard risks, but its conclusions also apply to other fields of risk management.     

Risk Assessment Can Be a Game‐Changing Information Technology—But Too Often It Isn't

The printing press was a game‐changing information technology. Risk assessment could be also. At present, risk assessments are commonly used as one‐time decision aids: they provide justification for a particular decision, and afterwards usually sit on a shelf. However, when viewed as information technologies, their potential uses are much broader. Risk assessments: (1) are repositories of structured information and a medium for communication; (2) embody evaluative structures for setting priorities; (3) can preserve information over time and permit asynchronous communication, thus encouraging learning and adaptation; and (4) explicitly address uncertain futures. Moreover, because of their “what‐if” capabilities, risk assessments can serve as a platform for constructive discussion among parties that hold different values. The evolution of risk assessment in the nuclear industry shows how such attributes have been used to lower core‐melt risks substantially through improved templates for maintenance and more effective coordination with regulators (although risk assessment has been less commonly used in improving emergency‐response capabilities). The end result of this evolution in the nuclear industry has been the development of “living” risk assessments that are updated more or less in real time to answer even routine operational questions. Similar but untapped opportunities abound for the use of living risk assessments to reduce risks in small operational decisions as well as large policy decisions in other areas of hazard management. They can also help improve understanding of and communication about risks, and future risk assessment and management. Realization of these opportunities will require significant changes in incentives and active promotion by the risk analytic community.     

The Use of Mental Models in Chemical Risk Protection: Developing a Generic Workplace Methodology

We adopted a comparative approach to evaluate and extend a generic methodology to analyze the different sets of beliefs held about chemical hazards in the workplace. Our study mapped existing knowledge structures about the risks associated with the use of perchloroethylene and rosin-based solder flux in differing workplaces. "Influence diagrams" were used to represent beliefs held by chemical experts; "user models" were developed from data elicited from open-ended interviews with the workplace users of the chemicals. The juxtaposition of expert and user understandings of chemical risks enabled us to identify knowledge gaps and misunderstandings and to reinforce appropriate sets of safety beliefs and behavior relevant to chemical risk communications. By designing safety information to be more relevant to the workplace context of users, we believe that employers and employees may gain improved knowledge about chemical hazards in the workplace, such that better chemical risk management, self-protection, and informed decision making develop over time.     

Tiered Approach to Resilience Assessment

Regulatory agencies have long adopted a three‐tier framework for risk assessment. We build on this structure to propose a tiered approach for resilience assessment that can be integrated into the existing regulatory processes. Comprehensive approaches to assessing resilience at appropriate and operational scales, reconciling analytical complexity as needed with stakeholder needs and resources available, and ultimately creating actionable recommendations to enhance resilience are still lacking. Our proposed framework consists of tiers by which analysts can select resilience assessment and decision support tools to inform associated management actions relative to the scope and urgency of the risk and the capacity of resource managers to improve system resilience. The resilience management framework proposed is not intended to supplant either risk management or the many existing efforts of resilience quantification method development, but instead provide a guide to selecting tools that are appropriate for the given analytic need. The goal of this tiered approach is to intentionally parallel the tiered approach used in regulatory contexts so that resilience assessment might be more easily and quickly integrated into existing structures and with existing policies.     

Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams

Probabilistic risk assessment (PRA) is a useful tool to assess complex interconnected systems. This article leverages the capabilities of PRA tools developed for industrial and nuclear risk analysis in community resilience evaluations by modeling the food security of a community in terms of its built environment as an integrated system. To this end, we model the performance of Gilroy, CA, a moderate‐size town, with regard to disruptions in its food supply caused by a severe earthquake. The food retailers of Gilroy, along with the electrical power network, water network elements, and bridges are considered as components of a system. Fault and event trees are constructed to model the requirements for continuous food supply to community residents and are analyzed efficiently using binary decision diagrams (BDDs). The study also identifies shortcomings in approximate classical system analysis methods in assessing community resilience. Importance factors are utilized to rank the importance of various factors to the overall risk of food insecurity. Finally, the study considers the impact of various sources of uncertainties in the hazard modeling and performance of infrastructure on food security measures. The methodology can be applicable for any existing critical infrastructure system and has potential extensions to other hazards.     

Is Epidemiology the Key to Cumulative Risk Assessment?

Although cumulative risk assessment by definition evaluates the joint effects of chemical and nonchemical stressors, studies to date have not considered both dimensions, in part because toxicological studies cannot capture many stressors of interest. Epidemiology can potentially include all relevant stressors, but developing and extracting the necessary information is challenging given some of the inherent limitations of epidemiology. In this article, I propose a conceptual framework within which epidemiological studies could be evaluated for their inclusion into cumulative risk assessment, including a problem formulation/planning and scoping step that focuses on stressors meaningful for risk management decisions, extension of the chemical mixtures framework to include nonchemical stressors, and formal consideration of vulnerability characteristics of the population. In the long term, broadening the applicability and informativeness of cumulative risk assessment will require enhanced communication and collaboration between epidemiologists and risk assessors, in which the structure of social and environmental epidemiological analyses may be informed in part by the needs of cumulative risk assessment.     

Risk Characterization for Nanotechnology

Nanotechnology is a broad term that encompasses materials, structures, or processes that utilize engineered nanomaterials, which can be defined as materials intentionally designed to have one or more dimensions between 1 and 100 nm. Historically, risk characterization has been viewed as the final phase of a risk assessment process that integrates hazard identification, dose‐response assessment, and exposure assessment. The novelty and diversity of materials, structures, and tools that are covered by above‐defined “nanotechnology” raise substantial methodological issues and pose significant challenges for each of these phases of risk assessment. These issues and challenges culminate in the risk characterization phase of the risk assessment process, and this article discusses several of these key issues and approaches to developing risk characterization results and their implications for risk management decision making that are specific to nanotechnology.     

Chemical and Radiation Environmental Risk Management: Differences, Commonalities, and Challenges

Driven by differing statutory mandates and programmatic separation of regulatory responsibilities between federal, state, and tribal agencies, distinct chemical and radiation risk management strategies have evolved. In the field this separation poses real challenges since many of the major environmental risk management decisions we face today require the evaluation of both types of risks. Over the last decade, federal, state, and tribal agencies have continued to discuss their different approaches and explore areas where their activities could be harmonized. The current framework for managing public exposures to chemical carcinogens has been referred to as a "bottom up approach." Risk between 10(-4) and 10(-6) is established as an upper bound goal. In contrast, a "top down" approach that sets an upper bound dose limit and couples with site specific As Low As Reasonably Achievable Principle (ALARA), is in place to manage individual exposure to radiation. While radiation risk are typically managed on a cumulative basis, exposure to chemicals is generally managed on a chemical-by-chemical, medium-by-medium basis. There are also differences in the nature and size of sites where chemical and radiation contamination is found. Such differences result in divergent management concerns. In spite of these differences, there are several common and practical concerns among radiation and chemical risk managers. They include 1) the issue of cost for site redevelopment and long-term stewardship, 2) public acceptance and involvement, and 3) the need for flexible risk management framework to address the first two issues. This article attempts to synthesize key differences, opportunities for harmonization, and challenges ahead.     

On the Selection of Distributions for Stochastic Variables

One of the main steps in an uncertainty analysis is the selection of appropriate probability distribution functions for all stochastic variables. In this paper, criteria for such selections are reviewed, the most important among them being any a priori knowledge about the nature of a stochastic variable, and the Central Limit Theorem of probability theory applied to sums and products of stochastic variables. In applications of these criteria, it is shown that many of the popular selections, such as the uniform distribution for a poorly known variable, require far more knowledge than is actually available. However, the knowledge available is usually sufficient to make use of other, more appropriate distributions. Next, functions of stochastic variables and the selection of probability distributions for their arguments as well as the use of different methods of error propagation through these functions are discussed. From these evaluations, priorities can be assigned to determine which of the stochastic variables in a function need the most care in selecting the type of distribution and its parameters. Finally, a method is proposed to assist in the assignment of an appropriate distribution which is commensurate with the total information on a particular stochastic variable, and is based on the scientific method. Two examples are given to elucidate the method for cases of little or almost no information.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Use of Multicriteria Decision Analysis to Support Weight of Evidence Evaluation

Weight of evidence (WOE) methods are key components of ecological and human health risk assessments. Most WOE applications rely on the qualitative integration of diverse lines of evidence (LOE) representing impact on ecological receptors and humans. Recent calls for transparency in assessments and justifiability of management decisions are pushing the community to consider quantitative methods for integrated risk assessment and management. This article compares and contrasts the type of information required for application of individual WOE techniques and the outcomes that they provide in ecological risk assessment and proposes a multicriteria decision analysis (MCDA) framework for integrating individual LOE in support of management decisions. The use of quantitative WOE techniques is illustrated for a hypothetical but realistic case study of selecting remedial alternatives at a contaminated aquatic site. Use of formal MCDA does not necessarily eliminate biases and judgment calls necessary for selecting remedial alternatives, but allows for transparent evaluation and fusion of individual LOE. It also provides justifiable methods for selecting remedial alternatives consistent with stakeholder and decision‐maker values.