The Concentration Term and Derivation of Cleanup Goals Using Probabilistic Risk Assessment

This communication examines the role of back-calculation in developing a cleanup goal from a probabilistic risk assessment. Although back-calculation is not always appropriate with a Monte Carlo analysis, if the target risk level is specified as a single value (e.g., 95% of the population must have a cancer risk below 10?5), then back-calculation can be used to solve for a cleanup goal that represents an average concentration for an exposure area consistent with the stated target risk. This rule applies in developing screening levels and in probabilistic risk assessments that examine the influence of uncertainty in the average concentration. Back-calculation is not used to develop cleanup goals when risks arising from variable concentrations are assessed, for example, when exposure areas are very small such as for some ecological receptors, or when exposure frequency is very low such as for tourist fishermen. In this case, the cleanup goal is derived from an iterative risk calculation considering various possible truncation values of the concentration distribution. A cleanup goal derived in this manner does not correspond to a required average, but rather represents the maximum concentration that should be left in the field. Finally, although single value target risk specifications are common today, there may be advantages to setting target risks for multiple percentiles of the population, complicating the effort to calculate a cleanup goal.     

Are all distributions of risk with the same 95thpercentile equally acceptable?

When evaluating a probabilistic health risk assessment, say at a hazardous waste site, risk managers need a risk management policy that distinguishes an acceptable distribution of risks to individuals in a population from an unacceptable one. If a risk manager decides that the distribution of risk for the status quo is unacceptable, then a risk assessor needs a way to compute cleanup targets, i.e., the risk assessor needs a policy statement against which to estimate distributions of exposure point concentrations which, if engineered at a site, will achieve an acceptable distribution of risk. Some regulatory agencies base acceptability on whether the 95^th percentile of the risk distribution falls at or below a given value, without considering the behavior of the rest of the distribution. As regulatory agencies adopt risk management policies for use with probabilistic risk assessments, we recommend that they base their new policies on two simultaneously binding constraints‐one on an upper percentile and one on the arithmetic mean of the distribution of risk‐in addition to other non‐risk criteria.     

Background levels of polycyclic aromatic hydrocarbons (PAH) and selected metals in new England urban soils

Polycyclic aromatic hydrocarbons (PAH) are byproducts of combustion and are ubiquitous in the urban environment They are also present in industrial chemical wastes, such as coal tar, petroleum refinery sludges, waste oils and fuels, and wood‐treating residues. Thus, PAHs are chemicals of concern at many waste sites. Risk assessment methods will yield risk‐based cleanup levels for PAHs that range from 0.1 to 0.7 mg/kg. Given their universal presence in the urban environment, it is important to compare risk‐based cleanup levels with typical urban background levels before utilizing unrealistically low cleanup targets. However, little data exist on PAH levels in urban, nonindustrial soils. In this study, 60 samples of surficial soils from urban locations in three New England cities were analyzed for PAH compounds. In addition, all samples were analyzed for total petroleum hydrocarbons (TPH) and seven metals. The upper 95% confidence interval on the mean was 3 mg/kg for benzo(a)pyrene toxic equivalents, 12 mg/kg for total potentially carcinogenic PAH, and 25 mg/kg for total PAH. The upper 95% confidence interval was 373 mg/kg for TPH, which exceeds the target level of 100 mg/kg used by many state regulatory agencies. Metal concentrations were similar to published background levels for all metals except lead. The upper 95% confidence interval for lead was 737 mg/kg in Boston, 463 mg/kg in Providence, and 378 mg/kg in Springfield.     

An extended multi-objective mixed integer programming for water resources management through possibility theory

In this study, we develop an extended multi-objective mixed integer programming (EMOMIP) approach for water resources management under uncertainty, in which the parameters are fuzzy random variables while the decision variables are interval variables. Furthermore, some alternatives are considered to retrieve the difference between the quantities of promised water-allocation targets and the actual allocated water. Then, the proposed EMOMIP for the problem is solved by a new method using fuzzy random chance-constrained programming based on the idea of possibility theory. This method can satisfy both optimistic and pessimistic decision makers simultaneously. Finally, a real example is given to explain the proposed method.     

Comparing and contrasting threat assessments of plant species at the global and sub-global level

Evidence-based assessments of extinction risk are established tools used to inform the conservation of plant species, and form the basis of key targets within the framework of the Global Strategy for Plant Conservation (GSPC). An overall picture of plants threat assessments is challenging due to the use of a variety of methodologies and range in scope from global to subnational. In this study, we quantify the state of progress in assessing the extinction risk of all land plants, determine the key geographic and taxonomic gaps with respect to our understanding of plant extinction risk, and evaluate the impact of different sources and methodologies on the utility of plant assessments. To this end, we have analyzed a cleaned dataset compiled from IUCN Red List of Threatened Species and Regional Red Lists. We reveal that there are assessments available for 89,810 distinct species or 25% of all accepted land plant species. However unlike with other major organismal lineages the bulk of the plant species assessments are derived from Regional Red Lists, and not the Global IUCN Red List. We demonstrate that this bias towards regional assessments results in distinct taxonomic and geographic strengths and weaknesses, and we identify substantial taxonomic and geographic gaps in the assessment coverage. With species that have been assessed in common at both global and regional levels, we explore the implications of combining threat assessments from different sources. We find that half of global and regional assessments do not agree on the exact category of extinction risk for a species. Regional assessments assign a higher risk of extinction; or underestimate extinction risk with almost equal frequency. We conclude with recommended interventions, but support the suggestion that all threat assessments should be pooled to provide more data and broaden the scope of threat assessments for monitoring progress towards GSPC targets.     

Prevalence of dermal pathway dominance in risk assessment of contaminated soils: A survey of superfund risk assessments, 1989–1992

Exposure to soil‐borne contaminants can occur through ingestion, inhalation and/or dermal absorption. A study was undertaken to assess the relative frequency with which dermal exposures are predicted to pose the greatest risk attributable to contaminated soils in Superfund risk assessments. Screening of over 200 risk assessments from the period 1989–1992 resulted in identification of 37 sites at which projected lifetime excess cancer risks attributed to dermal contact with soil were greater than the nominal regulatory threshold of 1.10^‐4. At 19 of these sites, the dermal/soil pathway is estimated to contribute the largest carcinogenic risk associated with surface soil contamination, and may therefore drive cleanup of that medium. At 9 of the sites, the dermal/soil pathway is predicted to present a higher carcinogenic risk than any other pathway. Chemical contaminant type and estimates of soil adherence and surface area exposed appear to be the primary factors that distinguish sites at which dermal/soil pathway carcinogenic risk estimates are elevated relative to other exposure pathways. Quantification of exposure parameters, especially those related to behavior, remains a significant need.     

Mathematical properties of the risk equation when variability is present

When random variables are used to represent variability, the risk equation has mathematical properties poorly understood by many risk assessors, variability represents the heterogeneity in a well‐characterized population, usually not reducible through further measurement or study. We follow the lead of most mathematicians in using random variables to represent and analyze variability. To illustrate the issues, we use LogNormal distributions to model variability.     

Extrapolation in Risk Assessment: Improving the Quantification of Uncertainty,and Improving Information to Reduce the Uncertainty

Risk assessments inevitably extrapolate from the known to the unknown. The resulting calculation of risk involves two fundamental kinds of uncertainty: uncertainty owing to intrinsically unpredictable (random) components of the future events, and uncertainty owing to imperfect prediction formulas (parameter uncertainty and error in model structure) that are used to predict the component that we think is predictable. Both types of uncertainty weigh heavily both in health and ecological risk assessments. Our first responsibility in conducting risk assessments is to ensure that the reported risks correctly reflect our actual level of uncertainty (of both types). The statistical methods that lend themselves to correct quantification of the uncertainty are also effective for combining different sources of information. One way to reduce uncertainty is to use all the available data. To further sharpen future risk assessments, it is useful to partition the uncertainty between the random component and the component due to parameter uncertainty, so that we can quantify the expected reduction in uncertainty that can be achieved by investing in a given amount of future data. An example is developed to illustrate the potential for use of comparative data, from toxicity testing on other species or other chemicals, to improve the estimates of low-effect concentration in a particular case with sparse case-specific data.     

Lithuanian cohort of Chernobyl cleanup workers: Cancer incidence follow-up 1986–2012

BackgroundCancer risks following radiation exposure in adulthood after Chernobyl are less studied compared to those after exposure in childhood. We aimed to evaluate cancer risk in the Lithuanian cohort of Chernobyl cleanup workers 26 years after their exposure in Chernobyl.MethodsStudy population (6707 men) was followed for cancer incidence upon return from Chernobyl till the end of 2012 by linkage procedure with the Lithuanian Cancer Registry and for migration and death – with Central Population Registry. The site-specific cancer risk in the cohort was estimated by calculating the standardised incidence ratio (SIR) with 95 % confidence interval (CI).ResultsA total of 596 cancer cases was observed in the cohort, against 584 expected (SIR 1.02; 95 % CI 0.94, 1.11). Only incidence of mouth and pharynx cancers was increased compared to the expected (SIR 1.41; 95 % CI 1.07, 1.86). Nevertheless, an increased risk of thyroid cancer was observed among cleanup workers who were younger than 30 years when entering the Chernobyl zone (SIR 2.90; 95 % CI 1.09, 7.72), whose radiation dose was above 100 milisievert (mSv) (SIR 3.13; 95 % CI 1.30, 7.52) and who had shorter duration of stay (SIR 2.30; 95 % CI 1.03, 5.13).ConclusionsOur findings are consistent with those observed in other cohorts of workers, namely, the increased risk of cancer sites related to behavioural factors. The increased risk of thyroid cancer among cleanup workers who were younger than 30 years when entering Chernobyl and whose radiation dose was above 100 mSv cannot exclude the association with the radiation exposure in Chernobyl.     

Human Health Risk Assessment at a Depleted Uranium Site

Human health risk assessments for depleted uranium are common for Department of Defense (DOD) sites since the metal has various military uses. At a training and experimental site, DU was evaluated in soil in order to make decisions regarding cleanup and future use of the site. At this site, concentrations were found to be protective of human health; DU is less toxic than uranium. Other data important to this decision were the type of receptors likely to be exposed, the amount of time spent by the receptor on-site, the acceptable yearly radiation dose, and other non-radiation associated effects to the kidney. Total uranium concentrations in soil were calculated for the 90th percentile and the 50th percentile. The highest soil concentration used as an exposure point was 3500 ug/g (90th percentile). Short exposure timeframes contributed to the risk results.     

Confidence intervals for directly standardized rates using mid‐p gamma intervals

Directly standardized rates continue to be an integral tool for presenting rates for diseases that are highly dependent on age, such as cancer. Statistically, these rates are modeled as a weighted sum of Poisson random variables. This is a difficult statistical problem, because there are k observed Poisson variables and k unknown means. The gamma confidence interval has been shown through simulations to have at least nominal coverage in all simulated scenarios, but it can be overly conservative. Previous modifications to that method have closer to nominal coverage on average, but they do not achieve the nominal coverage bound in all situations. Further, those modifications are not central intervals, and the upper coverage error rate can be substantially more than half the nominal error. Here we apply a mid‐p modification to the gamma confidence interval. Typical mid‐p methods forsake guaranteed coverage to get coverage that is sometimes higher and sometimes lower than the nominal coverage rate, depending on the values of the parameters. The mid‐p gamma interval does not have guaranteed coverage in all situations; however, in the (not rare) situations where the gamma method is overly conservative, the mid‐p gamma interval often has at least nominal coverage. The mid‐p gamma interval is especially appropriate when one wants a central interval, since simulations show that in many situations both the upper and lower coverage error rates are on average less than or equal to half the nominal error rate.     

Cleanup standards for petroleum hydrocarbons. Part 1. Review of methods and recent developments

Many states across the U.S. use the total petroleum hydrocarbon (TPH) measurement as a regulatory tool for setting cleanup standards for underground storage tank sites and other petroleum‐related sites requiring cleanup. In Part I of this article, alternative techniques for developing site‐specific cleanup standards for petroleum hydrocarbons are reviewed, including the use of chemical fingerprinting, constituent analysis, and risk assessment methods that address hydrocarbons found in the environment. New developments in standard setting for petroleum hydrocarbons are described, including risk‐based standards for hydrocarbon mixtures and ecological risk‐based approaches. In Part 2 of this article, the cost‐effectiveness and accuracy of the most commonly used of these approaches will be evaluated by comparing a generic TPH cleanup standards approach with site‐specific cleanup standards approaches for two actual sites in Washington State, a neighborhood gas station and a former bulk fuel storage facility.     

Role of Ecological Modeling in Risk Assessment

Ecological models are useful tools for evaluating the ecological significance of observed or predicted effects of toxic chemicals on individual organisms. Current risk estimation approaches using hazard quotients for individual-level endpoints have limited utility for assessing risks at the population, ecosystem, and landscape levels, which are the most relevant indicators for environmental management. In this paper, we define different types of ecological models, summarize their input and output variables, and present examples of the role of some recommended models in chemical risk assessments. A variety of population and ecosystem models have been applied successfully to evaluate ecological risks, including population viability of endangered species, habitat fragmentation, and toxic chemical issues. In particular, population models are widely available, and their value in predicting dynamics of natural populations has been demonstrated. Although data are often limited on vital rates and doseresponse functions needed for ecological modeling, accurate prediction of ecological effects may not be needed for all assessments. Often, a comparative assessment of risk (e.g., relative to baseline or reference) is of primary interest. Ecological modeling is currently a valuable approach for addressing many chemical risk assessment issues, including screening-level evaluations.     

Global conservation priorities for marine turtles

Where conservation resources are limited and conservation targets are diverse, robust yet flexible priority-setting frameworks are vital. Priority-setting is especially important for geographically widespread species with distinct populations subject to multiple threats that operate on different spatial and temporal scales. Marine turtles are widely distributed and exhibit intra-specific variations in population sizes and trends, as well as reproduction and morphology. However, current global extinction risk assessment frameworks do not assess conservation status of spatially and biologically distinct marine turtle Regional Management Units (RMUs), and thus do not capture variations in population trends, impacts of threats, or necessary conservation actions across individual populations. To address this issue, we developed a new assessment framework that allowed us to evaluate, compare and organize marine turtle RMUs according to status and threats criteria. Because conservation priorities can vary widely (i.e. from avoiding imminent extinction to maintaining long-term monitoring efforts) we developed a “conservation priorities portfolio” system using categories of paired risk and threats scores for all RMUs (n = 58). We performed these assessments and rankings globally, by species, by ocean basin, and by recognized geopolitical bodies to identify patterns in risk, threats, and data gaps at different scales. This process resulted in characterization of risk and threats to all marine turtle RMUs, including identification of the world''s 11 most endangered marine turtle RMUs based on highest risk and threats scores. This system also highlighted important gaps in available information that is crucial for accurate conservation assessments. Overall, this priority-setting framework can provide guidance for research and conservation priorities at multiple relevant scales, and should serve as a model for conservation status assessments and priority-setting for widespread, long-lived taxa.     

Parametric and jackknife confidence interval estimators for two-factor mating design genetic variance ratios

Summary Confidence interval estimators have not been defined for dominance to additive genetic variance () and average degree of dominance () for the nested, factorial, and backcross mating designs. The objective of this paper was to describe interval estimators for these parameters. Approximate F random variables were defined for expected mean square (EMS) ratios for linear models with one environmental effect. Approximate 1– parametric interval estimators were defined for and using these random variables. Random variables defined for linear models with no environmental effects are not approximately distributed as F random variables because common EMS are involved in the numerators and denominators of the EMS ratios. Delete-one jackknife (jackknife) interval estimators were defined for and for linear models with zero or one environmental effect(s); In transformed analysis of variance point estimates were used in pseudovalue estimators.Oregon Agricultural Experiment Station Technical Paper No. 8067     

Air Pollution from Industry and Traffic: Perceived Risk and Affect in the Moerdijk Region,The Netherlands

The aim of the present study was to compare the perceived risks of air pollution from industry and traffic in the Moerdijk region in The Netherlands, and to identify the demographic and psychometric variables that are associated with these perceived risks. We sent out a questionnaire and risk perceptions were explored using multiple regression models. The results showed that the perceived risks of industrial air pollution were higher than for those of traffic-related air pollution. The perceived risk of industrial air pollution was associated with other variables than that of traffic. For industry, the psychometric variable affect prevailed. For traffic-related air pollution, the demographic variables age and educational level prevailed, although affect was also apparent. Which source was considered as the major source—traffic or industry—depended on a high risk perception of industrial air pollution, and not on variation in risk perception of traffic-related air pollution. These insights can be used as an impetus for the local risk management process in the Moerdijk region. We recommend that local authorities consider risk perception as one of the targets in local risk management strategies as well.     

Avian exposure and bronchogenic carcinoma.

OBJECTIVE--To investigate the association between bird keeping and risk of lung cancer. DESIGN--Case-control study asking detailed questions on exposure to domestic birds and other pets, smoking, and various demographic and potentially confounding variables. SETTING--District general hospital; current admissions interviewed in hospital or recent admissions interviewed at home. PATIENTS--143 patients with lung cancer, 143 controls with heart disease, and 143 controls with orthopaedic conditions individually matched for age, sex, date of admission, and current or past admission. MAIN OUTCOME MEASURES--Odds ratios for lung cancer in relation to various aspects of bird keeping, after adjustment for smoking and other relevant confounding variables. RESULTS--Risk of lung cancer was not significantly associated with household exposure to pet birds at any time or at various specific periods in life, or to keeping large numbers of birds. For specific types of birds no association was seen for living in households with budgerigars or canaries but risk was significantly associated with keeping pigeons (odds ratio 3.53, 95% confidence interval 1.56 to 7.98). This remained significant after regression analysis to account for confounding variables (3.9, 1.2 to 12.62) in both sexes and all age groups. CONCLUSION--Bird keeping may confer some risk of lung cancer but the relation is not as strong as previously reported.     

Attendance at cultural events,reading books or periodicals,and making music or singing in a choir as determinants for survival: Swedish interview survey of living conditions.

OBJECTIVES: To investigate the possible influence of attendance at cultural events, reading books or periodicals, making music or singing in a choir as determinants for survival. DESIGN: A simple random sample was drawn of 15,198 individuals aged 16-74 years. Of these, 85% (12,982) were interviewed by trained non-medical interviewers between 1982 and 1983 about cultural activities. They were followed up with respect to survival until 31 December 1991. SETTING: Swedish interview survey of living conditions comprising a random sample of the adult Swedish population. SUBJECTS: 12,675 people interviewed between 1982 and 1983. MAIN OUTCOME MEASURES: Survival of subjects after controlling for eight confounding variables: age, sex, education level, income, long term disease, social network, smoking, and physical exercise. RESULTS: 6,301 men and 6,374 women were followed up; 533 men and 314 women died during this period. The control variables influenced survival in the expected directions except for social network for men; a significant negative effective was found when the analysis was made separately for men and women. We found an influence on mortality when the eight control variables were controlled for in people who rarely attended events compared with those attending most often, the relative risk being 1.57 (95% confidence interval 1.18 to 2.09). CONCLUSION: Attendance at cultural events may have a positive influence on survival. Long term follow up of large samples with confounders that are well controlled for and with the cultural stimulation more highly specified should be used to try to falsify the hypothesis before experiments start.