Final Program - Society for Risk Analysis

T2-A.4 L’Orange Seigo S, Wallquist L, Dohle S, Siegrist M; slorange@ethz.chETH ZurichTHE POTENTIALLY ALARMING EFFECT OF COMMUNICATINGCCS MONITORINGAn online experiment (N = 200) was conducted to investigate the influenceof information about monitoring measures at CO2 storage sites on laypeople’s perceptionsof Carbon Capture and Storage (CCS). One experimental group receivedonly a basic introductory text, while the other group received additional informationabout CO2 monitoring. Men in the monitoring condition exhibited significantly loweracceptance, significantly higher levels of negative affect, and marginally higher riskperception of CCS; no significant effects were observed in the female subsample.We conclude that information about monitoring activities does not exert a reassuringeffect and may even be alarming when actively communicated. The gender differencemay be explained by a difference in the salience of mental concepts between men andwomen regarding CCS. Implications for communication about CCS and for futureresearch are discussed.T2-C.2 Lam JL, Fox MA, Burke TA; juleenlam@gmail.comJohns Hopkins University, Bloomberg School of Public HealthDEVELOPING A BAYESIAN APPROACH TO DOSE RESPONSE AS-SESSMENT: AN APPLICATION TO TRIHALOMETHANES IN DRINK-ING WATERPervasive uncertainty is a dominant analytical difficulty that continues to hinderthe EPA’s risk assessment process for setting standards for environmental contaminants,particularly within the dose-response step. Currently, the EPA handles thisby applying deterministic factors referred to as safety or uncertainty factors. Thisapproach has long been criticized as arbitrary, obscuring the true uncertainty, andlimiting the ability of policy-makers to make adequately informed risk managementdecisions. We propose a hierarchical Bayesian model approach to synthesize evidencefrom toxicological and epidemiological studies, allowing for explicit statement of uncertaintyassumptions in the prior distributions, and pre-processing data using BayesianModel Averaging (BMA) to account for model uncertainty. We apply this modelto a case study of chloroform, a disinfection byproduct, in drinking water. We usethe same data set considered by the EPA when setting their regulatory standardsfor chloroform, exploring four different health outcomes that were either cancer orconsidered pre-cursors to cancer. Final model estimates demonstrated that incorporatingmore scientific information into the priors had minimal impacts on mean estimates,but reduced the uncertainty surrounding the final estimates. Benchmark dose(BMD) and lower-bound benchmark (BMDL) dose estimates from the model weremostly lower than those estimated by the EPA, indicating that not considering thefull body of scientific evidence fails to capture the true uncertainty surrounding the132final estimate. As a result, Maximum Contaminant Level Goal (MCLG) estimates usingthe Bayesian model were consistently lower than EPA estimates, and in particularwere lower than the MCLG standard for chloroform currently in place. This Bayesianmodel provide an alternative approach to incorporating and quantifying varioussources of uncertainty in the dose-response step, and may be applicable in otheraspects of risk assessment.M3-H.2 Langbehn W; bob.ross@dhs.govHomeland Security Institute/ANSERASSESSMENT OF COMPLEX ADAPTIVE SYSTEM THEORY FORHOMELAND SECURITY RISK MANAGEMENTThis presentation will provide the results of a preliminary examination of thestate of the art and knowledge in Complex Adaptive System (CAS) theory, risk analysisand risk management strategies. This study was driven by the dual beliefs that mostof the problems falling within homeland security arise within CASs and that many ofthe most widely used risk analytic methodologies are either inadequate for use withCASs or are being misapplied therein. Risk assessment leading to risk managementas a means for informing decisions is central to homeland security planning, and policymaking.Prevailing homeland security risk problem designs and analytical methodsinadequately address important complexities that affect risk assessments and thereforerisk management. Addressing threats to our security requires considering thecomplex interaction between the homeland security enterprise actors and the bodyof threats. For example, terrorism risk assessments require an estimation of behaviorsfor both sides over time and consideration of their opposing capabilities. Analyzingthese complex dynamic interactions, many of which are not well understood, requiressimplification. Unfortunately, too much simplification produces results which may beuseless, or even worse, badly misleading. Complex Adaptive System concepts - theirtheoretic underpinnings and potential applications — may present opportunities forimproving the quality of homeland security risk management. Accordingly, the purposeof this task is to research the current “state of the art” with respect to both thetheory and application of CAS concepts to terrorist-driven risk assessments and providean evaluation of its potential utility as a tool for enhancing homeland security riskmanagement. This paper and presentation are intended to alert the academic researchcommunity to the issue, to emphasize DHS interest in the topic and hopefully to spurfurther exploratory and developmental work in applying CAS theory and practice toimprove DHS risk management.