Final Program - Society for Risk Analysis

W4-I.1 Beach RH, McCarl BA, Ohrel SB, DeAngelo BJ, Ross MT; rbeach@rti.orgRTI InternationalMODELING U.S. AGRICULTURAL RESPONSE UNDER CLIMATECHANGEClimate change will affect future agricultural production through changes in atmosphericcarbon dioxide levels, average and extreme temperatures, precipitation patternsand intensity, and the frequency and severity of extreme events such as flooding,drought, hail, and hurricanes. Assessing the impact of the climatic changes oncrop yield, output levels and commodity prices, however, also depends on behavioraland adaptive responses in the agricultural sector. In this study, we estimate potentiallong-term implications of climate change on U.S. landowner decisions regarding landuse, crop mix, and production practices, combining a crop process model (EPIC) tocapture the changes in the physical system with a forward-looking dynamic economicmodel of the U.S. forestry and agricultural sector (FASOM). Climate-induced changesin crop yields simulated with EPIC were used as inputs into the stochastic version ofFASOM. We observe both substantial increases and decreases in crop yields. In general,yields increase in northern areas relative to southern areas. The patterns of simulatedyield changes for a given climate scenario, however, show significant intraregionalvariation depending on the type of crop, irrigation status, and changes in wateravailability, nutrient availability, as well as many other factors. We model crop allocationdecisions based on the relative returns and risk associated with alternative croppingpatterns under future climate scenarios. Our results show substantial changes inregional crop acreage allocation and production patterns as producers switch cropsand practices in response to changes in expected profitability and risk under climatechange, which in turn may inform agricultural adaptation measures. Finally, impactsestimated using FASOM are incorporated within the Applied Dynamic Analysis ofthe Global Economy (ADAGE) dynamic computable general equilibrium model toassess interactions with other sectors and macroeconomic impacts.60T3-G.4 Beaudrie CEH, Kandlikar M, Satterfield T, Herr Harthorn B; christian.beaudrie@gmail.comInstitute for Resources, Environment and Sustainability, University of British Columbia; Center forNanotechnology in Society, University of California Santa BarbaraEXPERT OPINION AND LIFECYCLE REGULATION FOR EMERG-ING NANOMATERIALSEngineered nanoscale materials (ENMs) present a difficult challenge for riskassessors and regulators. Assessment of risks along the life cycle of nanomaterials islimited both by a lack of inventory data (since production information is scarce) andby the paucity of impact data (since exposure and toxicity data is lacking). Continuinguncertainty about potential exposure and toxicity of EMNs implies that expert opinionwill play an important role in assessing and regulating risk. This paper employsdata from a recent survey of nanotechnology experts (n=430 nano-scientists andengineers, toxicologists and regulators) alongside a comprehensive review of existingregulatory options across the lifecycle of nanomaterials. We find, overall, differencesin opinions among classes of experts about the lifecycle risk of nanomaterials; differentexpert views of responsibility and preparedness for managing any risks posedby nanomaterials; and differing perspectives on barriers to implementing a life cycleapproach to the regulation of nanomaterials and nano-based products.W4-C.4 Becker RA, Moran E, Fensterheim R, Pottenger LH; rick_becker@americanchemistry.comAmerican Chemistry CouncilRECOMMENDATIONS FOR RETOOLING IRISWe now know more than ever about biological systems, modes by which chemicalsinteract with these and dose-dependency of effects which transition from nil (homeostasis)to adaptation to adverse. Yet in IRIS assessments such knowledge seemsnever enough to supersede defaults. Criticisms of IRIS include overreliance on assumptionsinstead of data, inconsistent data evaluation/study integration methodsand opaque justifications for conclusions. Our retooling recommendations involveimprovements in data acquisition, data evaluation, risk determination, and transparency.Problem formulation is key for data acquisition; if critical data needs are identified,a process and schedule can be agreed. Meaningful dialogue with stakeholdersduring problem formulation should focus assessments on key issues and enable developmentof relevant peer-review charge questions to evaluate these. Retooling dataevaluation requires consistent application of uniform criteria for determining methodvalidity, study reliability, data quality, and criteria for establishing cause and effect,coupled with a hypothesis-based weight of evidence framework for mode of actionevaluation, including evaluation of default(s). In risk determination, modernizationmeans selecting appropriate dose-response methods and conducting quantitative estimatesof central tendency for population probability risk distributions, not just upperbounds. Restructuring and enhancing public comments and peer-review processesare also needed to improve transparency and scientific integrity. Enhanced considerationof scientifically relevant public comments by the independent scientific peerreviewers, and documentation that an assessment was revised to adequately addresspeer-review findings and recommendations, should be considered. Given the importanceof IRIS assessments to EPA program offices, other federal agencies, states, andprivate & public sector impacts, retooling along the lines of our recommendations iswarranted.