systems against possible terrorist attacks. However, hardening a significant fraction ofa large, complex infrastructure network is typically not cost-effective. There is there<strong>for</strong>ean urgent need <strong>for</strong> methods of vulnerability analysis that take robustness andresilience explicitly into account, by highlighting those few sources of vulnerabilitythat are most likely to result in cascading failures (i.e., poor robustness to withstanddisruptions) and/or long restoration times (i.e., poor system resilience). Cascadingfailures have been historically a major unsolved problem <strong>for</strong> complex networks suchas electricity systems, but recent developments in probabilistic analysis of cascadingfailure have made it possible to take cascading failures into account in methodsof vulnerability assessment. Moreover, methods of vulnerability analysis can also bedesigned to highlight those vulnerabilities that are likely to lead to disproportionatelylong restoration times. In this research, we extend an existing method <strong>for</strong> identifyingnear-optimal interdiction strategies in electricity networks. Specifically, we analyzethe impact of cascading failures on system vulnerability in a probabilistic manner;take restoration time into account, making it possible <strong>for</strong> decision makers to maximizeresilience; and use the resulting method to examine the effectiveness and costeffectivenessof possible defensive investments. In particular, the use of methods thataccount <strong>for</strong> restoration time and cascading failure makes it possible to evaluate theeffectiveness not only of target hardening, but also of alternative mitigating strategies,such as improving resilience by decreasing restoration times (e.g., through stockpilingof spares), or increasing the capacity in crucial parts of the network (to reduce thepotential <strong>for</strong> cascading failure).180M2-E.3 Taylor CM, Pollard SJT, Rocks SA, Smith MC; c.taylor@cranfield.ac.ukCranfield UniversityENVIRONMENTAL RISK MANAGEMENT AND ECONOMIC PER-FORMANCE OF POLICY INSTRUMENTS: A STRATEGIC ANALYSISOF UK EXPERIENCE SINCE 1997This research provides a strategic analysis of a sample of UK environmentalpolicies, providing new evidence of what works when and why, to in<strong>for</strong>m the deliveryof better policy and regulation. Since the 1997 General Election innovative policyinstruments have been implemented in the UK moving beyond “command and control”regulation to utilise economic, in<strong>for</strong>mation based and voluntary approaches.Such approaches manage environmental risks whilst enabling businesses to competeand innovate*. However, they may not be appropriate <strong>for</strong> all sectors of the economy,or <strong>for</strong> high impact risks with high levels of social concern**. Since 2010 the UKCoalition Government has renewed the drive <strong>for</strong> regulatory re<strong>for</strong>m whilst aiming tobe the “greenest government ever”. This research takes stock of recent experienceto help achieve these objectives. Environmental policies targeted at a range of environmentalrisks were selected to provide 30 case studies illustrating direct regulation,economic instruments, education and advice, co-regulation, self-regulation, and technology/investmentprogrammes. Each policy was characterised according to targetedactor, policy instruments used, economic impact and impact on targeted environmentalrisk. Evidence was drawn from expert interviews and academic and gray literature.Correlations between instrument type and other characteristics were analysed. Theresearch tests existing theories of what works when and why, and suggests whereinnovative approaches may be used in future. A programme of research will developthese insights into a policy development framework to be utilised by the UK Department<strong>for</strong> Environment Food and Rural Affairs during <strong>for</strong>thcoming regulatory re<strong>for</strong>minitiatives. *Gunnningham & Sinclair (2002). Leaders and laggards. Next generationenvironmental regulation; ** Pollard et al (2004). Characterizing environmental harm:Developments in an approach to strategic risk assessment and risk management. <strong>Risk</strong><strong>Analysis</strong>, 24(6).P.111 Teuschler LK, Aume LS, Rice GE, Simmons JE, Pressman JG, NarotskyMG, Speth TF, Miltner RJ, Hunter ES, Richardson SD; teuschler.linda@epa.govUS Environmental Protection Agency, BattelleA STATISTICAL APPROACH FOR JUDGING STABILITY OF WHOLEMIXTURE CHEMICAL COMPOSITION OVER TIME FOR HIGHLYCOMPLEX DISINFECTION BY-PRODUCT MIXTURES FROM EPA’SFOUR LAB STUDYChemical characterization of complex mixtures and assessment of stabilityover time of the characterized chemicals is crucial both to characterize exposure andto use data from one mixture as a surrogate <strong>for</strong> other similar mixtures. The chemicalcomposition of test mixtures can vary due to natural variations of the collected environmentalmixture, concentration procedures, preparation of the mixture <strong>for</strong> testing,and chemical reactions during storage; these variations can affect toxicity. Thispresentation describes a statistical approach <strong>for</strong> evaluating chemical stability of highlycomplex disinfection by-product (DBP) mixtures resulting from disinfection of waterconcentrates used in EPA’s Four Lab multigenerational rodent bioassay. ComplexDBP mixtures were produced by concentrating natural source water with reverse osmosismembranes, storing the concentrate in 16 drums, and chlorinating the concentrateprior to placement on animal cages. At time intervals dictated by water demand,concentrate was chlorinated. Chemical analyses were conducted <strong>for</strong> each chlorinationevent; concentrate was sampled prior to use (day 0), at various time periods fromarbitrarily selected cages, and upon removal from cages. Mixed linear models wereused to evaluate stability of 44 individual DBPs, total organic halide (TOX), and 18DBP mixture subgroups across and within drums, and over time. Three hypothesistests evaluated whether: average chemical concentrations were stable across drumsover time; concentrations were stable within drums over time; and chlorination eventswere reproducible across drums on day 0. A judgment of instability required a >20%change in chemical concentrations from Day 0 to Day 14 or a >20% coefficient of
variation on Day 0. Results showed a high degree of stability and reproducibility <strong>for</strong>32 single DBPs, TOX, and 11 DBP mixture subgroups, including the halomethane,haloacid, and haloaldehyde chemical classes. (The views expressed in this abstract donot necessarily reflect the views or policies of the US EPA.)W2-D.1 Thekdi SA, Lambert JH; thekdi.s@gmail.comUniversity of VirginiaRISK MODELS AND NEGOTIATION ANALYSIS FOR LAND DEVEL-OPMENT ADJACENT TO INFRASTRUCTURE SYSTEMS<strong>Risk</strong>-in<strong>for</strong>med decision making <strong>for</strong> the protection of transportation, energy,communications, water, emergency services, and other infrastructures from adjacentland development is an essential need. The issues include diverse technology andadministrative remedies; large-scale and distributed assets; multiple owners and stakeholders;diverse nature of stakeholders, constraints and competing objectives; uncertaintiesin <strong>for</strong>ecasts, time horizon, schedule, and cost; and needs <strong>for</strong> agency transparencyand accountability in the prioritization and programming of investments. Theproblem calls <strong>for</strong> knowledge across several domains including risk analysis, lifecycleanalysis, scenario analysis, impact analysis, reliability modeling, multi-criteria analysis,and negotiation analysis. This presentation will develop risk and decision models thataddress risk of land development adjacent to infrastructure systems, testing the modelswith agencies responsible <strong>for</strong> a 6000-mile multimodal transportation network. Themodels will address a time horizon of about ten years, which is longer than annualor biannual budget cycles and shorter than long-range investment planning. The firstpart of this ef<strong>for</strong>t develops predictive models to estimate time-to-develop <strong>for</strong> milelongsections of corridor. The second part of this ef<strong>for</strong>t refines a scenario analysisto describe the impact of various scenarios on the time to develop. The third part ofthis ef<strong>for</strong>t per<strong>for</strong>ms negotiation analysis to support regulators/planners, localities,infrastructure owner/operators, and developers in coordinated risk management ofland development. This research has led the National Research Council to evaluatebest practices, methods, and tools that support transportation agencies to manage therisk of land development.W1-D.2 Thompson MP, Calkin DE; mpthompson02@fs.fed.usUS Forest ServiceADVANCEMENTS IN INTEGRATED WILDFIRE RISK ASSESSMENTFederal wildfire management within the United States continues to increase incomplexity, as the converging drivers of increased development, past managementpractices, and a changing climate magnify threats to human and ecological values andplace additional stress on limited fiscal resources. Further amplifying wildfire managementcomplexities are manifold sources of uncertainty, including variability surroundingfire occurrence and behavior, limited understanding of the spatiotemporaldynamics of ecological responses to fire, and limited resource value measures to guideprioritization across resources threatened by fire. In this presentation we will reviewprogress towards identification and characterization of uncertainties and the incorporationof this in<strong>for</strong>mation into integrated wildfire risk assessment frameworks to supportdecision-making. First, we will review a recently developed typology of uncertaintiescommon to wildfire decision-making and highlight the most salient sourcesof uncertainty. Second, we will describe the expanding role of spatially explicit burnprobability modeling as state-of-the-art exposure analysis, and illustrate the applicationof burn probability modeling to support strategic fuel reduction treatments aswell as active wildfire incident management. Third, we will discuss how our limitedunderstanding of fire effects poses challenges to quantifying risk, especially <strong>for</strong> nonmarketresources, and how we have relied on systematic elicitation of expert judgmentto advance wildfire effects analysis. We will provide examples from recent andongoing integrated risk assessments ranging from local to national planning scalesand describe their use <strong>for</strong> in<strong>for</strong>ming on-the-ground management and strategic policydevelopment. Lastly we will discuss remaining barriers to broader adoption of riskmanagement principles within federal wildfire management.M3-C.1 Thran BH, Intano GI, McAtee MJ; randbthran@hotmail.comArmy Institute of Public HealthNEED DRIVES DEVELOPMENT - ARMY BIOLOGICAL MILITARYEXPOSURE GUIDELINES (BMEGS)The U.S. Army Public Health Command (USAPHC) published risk assessmentguidance in 2009 <strong>for</strong> assessing exposures to aerosolized microbial pathogens fromenvironmental, occupational (i.e., laboratory accident), or intentional (e.g., terrorist)releases. The development of guidance supplements <strong>for</strong> specific areas continues andthey provide military public health relevant technical in<strong>for</strong>mation in the emerging areaof microbial risk assessment from non-traditional exposures. A critical proceduralgap is the ability to integrate mechanistic knowledge dose-response relationships intothe military risk assessment matrix used to categorize population-level health and operationalrisks. A team of risk analysts at the USAPHC have developed procedures toderive Biological Military Exposure Guidelines (BMEGs) <strong>for</strong> pathogens in air or waterthat represent health-protective or safe-sided estimates <strong>for</strong> certain health effects.Standardized data review and analysis should facilitate efficient derivation of BMEGs.An additional outcome of the BMEG derivation process is the identification of datagaps that can be used to fuel model-directed research. Directed research will beginto close current data gaps, reduce uncertainty about the nature and magnitude ofmicrobial risks, and improve confidence of future BMEGs. A phased approach toBMEG development is being implemented due in large part because the concept ofmicrobial exposure guidelines is so new. Preliminary BMEGs based on available scientificevidence and models can be useful decision criteria, if needed today and thereis adequate confidence in their level of protection/prediction. Interim and <strong>Final</strong>181
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WK9: Eliciting Judgments to Inform
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M2-C.1 Abraham IM, Henry S; abraham
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serious accident of the Tokyo Elect
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inter-donation interval to mitigate
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Fukushima nuclear accident coverage
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W1-C.1 Goble R, Hattis D; rgoble@cl
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stakeholders. The utility of this m
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P.122 Hosseinali Mirza V, de Marcel
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