Final Program - Society for Risk Analysis

W2-F.4 Gerst MD, Wang P, Roventini A, Dosi G, Howarth RB, Borsuk ME;mark.borsuk@dartmouth.eduDartmouth CollegeAGENT-BASED MODELLING OF THE LINKED ENERGY, ECONOM-IC, AND CLIMATE SYSTEM FOR SCENARIO GENERATION ANDROBUST DECISION-MAKINGSociety’s response to climate change is a global, collective decision-making problemunprecedented in scale and complexity. Formally analyzing the role of a nontrivialnumber of stakeholders in shaping climate policy has been elusive because theinherent heterogeneity precludes tractable analysis by traditional models. An alternativeapproach is represented by agent-based modeling, which employs the concept ofdiscrete actors, each possessing a set of defining characteristics and behavioral rules.Rather than focusing on equilibrium or rational choice outcomes, agent-based modelsare primarily concerned with the evolution of large-scale properties that naturally‘emerge’ from a system of heterogeneous, boundedly rational agents. We have beendeveloping a multi-level, agent-based model that simulates both international negotiationand the domestic dynamics of the economy, energy, and climate change. Ratherthan claiming predictive precision, the objective of our model is to support robustdecision-making under uncertainty by serving as a policy and scenario discovery tool.In the first capacity, policy formation is endogenous to the model and allows for investigationof the co-evolution of policy formation and system structure. This allowsone to address questions such as, “What are the likely enhancing or retarding factorsfor minimizing climate risks?” In the second capacity, as a scenario discovery tool, themodel allows one to engage in fully integrated scenario creation for exogenously suppliedpolicies. A relevant question is, “What are the conditions under which a givenpolicy performs poorly?” A particularly useful aspect of the scenario discovery modeis that policy solutions from other modelling frameworks can be used as inputs, providinga test of policy robustness. This makes agent-based modelling an importantcomplementary tool in the risk analyst’s toolbox.P.126 Gilmore EA, Moore A, Murphy BN, Adams PJ; gilmore@umd.eduUniversity of Maryland, Carnegie Mellon UniversityVARIABILITY IN AIR QUALITY MODELS INFLUENCES SOCIALCOST ESTIMATES FOR AIR EMISSIONSChoosing between alternative products, processes and policies requires credibleinformation about both the private and social costs. For air quality, an impact pathwayapproach is frequently employed to estimate this social cost. This entails convertingthe emissions to ambient concentrations, translating the concentrations to theirequivalent human health effects and applying willingness to pay estimates to avoidthese outcomes. Since this approach can be time consuming, literature values are usedin many analyses. The assumptions in the air quality models that are used to derive104the literature values, however, are rarely evaluated and may introduce error. Here, wedevelop new estimates of the social cost for air emissions in $/ton through an impactpathway approach. Using a ‘state of science’ 3-D chemical transport model, the ParticulateMatter Comprehensive Air Quality Model with extensions (PMCAMx), wemodel changes in fine particulate matter (PM2.5) from emission precursors for twourban and two rural sites in the summer and the winter for area and point sources. Wecalculate social costs that range from two to more than ten times higher than othervalues in literature for both reactive and non-reactive compounds, suggesting thatmodel variability in both transport and chemistry can have an important influence onthe estimates. Applying new models that reflect an improved understanding of theformation of secondary organic aerosols (SOA), we find that the social costs for thenon-methane hydrocarbons precursors can also vary by a factor of ten depending onthe formation mechanism. Our results suggest caution in the use of literature valuesfor the social cost of air quality emissions for benefit-cost analysis and externalitypricing.M2-H.1 Gilmour L, Rath C, Kolasky RP; lillian.gilmour@hq.dhs.govUS Department of Homeland Security, Office of Risk Management and AnalysisTOMORROW’S GOVERNMENT: BUILDING A RISK MANAGEMENTCULTURE AT THE DEPARTMENT OF HOMELAND SECURITYIn accordance with the Department of Homeland Security’s (DHS) QuadrennialHomeland Security Review, homeland security is considered tantamount to managingrisks to the Nation. Instituting a risk management program is about establishingefficient and effective processes throughout an organization that allows the promulgationand use of risk information to inform many types of decisions. It is also aboutbuilding a culture of risk management and changing the way members of an organizationthink about risk. Working to instill a culture of risk management is an importantaspect of any organization’s risk management efforts, and DHS is using a multiprongedapproach to promote risk management concepts and institutionalize riskmanagement practices throughout the organization. DHS is currently building participationin risk management decisions through a central governing body called theRisk Steering Committee, developing a risk management training program, conveyinga common language through a risk lexicon, distributing guidance on risk managementpractice, and providing tailored risk analysis and consultation to partners. While thereis much work to be done, in this session we will discuss some of the endeavors DHShas embarked upon and how DHS continues to strive for a risk management culture.In addition, we will discuss some of the challenges and lessons learned encounteredduring the implementation of a risk management program at DHS.