We begin this issue with a special series of four articles about mining-related risks. Many of these risks date back to the 19th century when large scale mining helped spur industrialization and urbanization in Europe and North America. Please read Engineering Area Editor Yacov Haimes's introduction immediately following this editorial for more detail and perspective about these articles.(1) In the rest of this issue, three articles examine different kinds of dietary risk. Funded by the USAID, C.M. Jolly et al. examine knowledge and perceptions of farmers associated with AF ingestion in Benin, West Africa. AFs are a group of extremely toxic metabolites produced by the fungi Aspergillus flavus and A. paraticus., and human ingestion is highly likely in Benin during the production of groundnuts and maize. After describing instances of hundreds of deaths, the authors surveyed 181 farmers to assess their understanding of the impacts on human and animal health. Gender and education seem to be dominating factors in the perception of barriers to mitigating the effects of AF. Male and older farmers are more aware of the risk but also of the benefits of producing and marketing groundnuts. Another dietary risk is from ingestion of acrylamide, a neurotoxin classified as a probable carcinogen to humans by the International Agency for Research on Cancer (IARC). Acrylamide can be formed by heating of bread, biscuits, crackers, and breakfast cereals. Enda Cummins et al. focus on what they label the “buoyant” market for French fries in Ireland. They develop a risk assessment model using Monte Carlo simulation in order to estimate the likely human exposure to acrylamide. The authors point to the need for strict control of cooking conditions (correlation coefficient of 0.42 and 0.35 for frying time and temperature, respectively) and blanching procedures (correlation coefficient −0.25) to reduce acrylamide formation. Understanding dietary risks from pesticides is an increasing important public health issue. Marc Kennedy and Andy Hart raise the issue of cumulative measurement errors in assessing pesticide concentration in dietary risk assessments. They propose and test a Bayesian method for assessing cumulative impacts of variability and uncertainty on final risk assessments. The remaining three articles in the issue deal with hurricane forecasting, transit vessel risks and decision-making influences. Seung Ryong Han et al., aim to improve the predictive accuracy of hurricane power outage forecasts. The authors assert that prior studies have developed regression models for estimating the number of power outages in advance of an approaching hurricane. However, these approaches have sometimes not been applicable or have had low predictive accuracy. Their paper offers a generalized additive model (GAM), which they demonstrate provides more accurate results in the Gulf Coast region than prior models. The results of GAM models, however, in the editor's experience, can sometimes be difficult to interpret. The Strait of Istanbul is a narrow body of water linking Asia and Europe (Black Sea and Mediterranean Sea). Ozgecan Uluscu et al. note that annually more than 55,000 ships pass through this congested and difficult to navigate waterway, and roughly 20 percent carry dangerous cargo. They build a model based on probabilistic assessments of accident instigators, situations, consequences and historical data as well as interviews with subject-matter experts. They use scenario analysis to study the behavior of the accident risks, with respect to changes in the surrounding geographical, meteorological and traffic conditions. Finding that local traffic density and pilotage (pilot or tugboat) are main factors affecting the risks, the authors point out that allowing more vessels into the Strait will increase risks to extreme levels. Conversely, scheduling changes that would reduce risks may cause major increases in average vessel waiting times. The result is a policy dilemma. Decision-makers' understanding of risk information is critical to their ability to make informed policy decisions. In a study funded by the National Science Foundation, Nathan Dieckmann and his colleagues from Decision Research explore how lay decision-makers with varying numerical abilities use and trust quantitative likelihood assessments and narrative evidence related to forecasts. They find that people who are more numerate focus more on likelihoods (e.g. there is a 30% chance of an event occurring) whereas the less numerate rely more on narrative evidence, implying that risk forecasters need to take into account the types of information that decision-makers find easiest to evaluate in reporting their results. The issue concludes with a book review by Lisa Robinson of Winston Harrington et al.'s edited volume, Reforming Regulatory Impact Analysis (2009). Robinson finds that the case studies, insightful critiques and recommendations in the book are useful to those interested in the connection between risk assessment and risk management decisions related to EPA's major regulations.
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Open Access
Jan 1, 2011
Daniel L Millimet + 1
