Optimization of Sampling for Monitoring Chemicals in the Food Supply Chain Using a Risk-Based Approach: The Case of Aflatoxins and Dioxins in the Dutch Dairy Chain

Food safety monitoring faces the challenge of tackling multiple chemicals along the various stages of the food supply chain. Our study developed a methodology for optimizing sampling for monitoring multiple chemicals along the dairy supply chain. We used a mixed integer nonlinear programming approach to maximize the performance of the sampling in terms of reducing the risk of the potential disability adjusted life years (DALYs) in the population. Decision variables are the number of samples collected and analyzed at each stage of the food chain (feed mills, dairy farms, milk trucks, and dairy processing plants) for each chemical, given a predefined budget. The model was applied to the case of monitoring for aflatoxin B₁/M₁(AFB₁/M₁) and dioxins in a hypothetical Dutch dairy supply chain, and results were calculated for various contamination scenarios defined in terms of contamination fraction and concentrations. Considering various monitoring budgets for both chemicals, monitoring for AFB₁/M₁ showed to be more effective than for dioxins in most of the considered scenarios, because AFB₁/M₁ could result into more DALYs than dioxins when both chemicals are in same contamination fraction, and costs for analyzing one AFB₁/M₁ sample are lower than for one dioxins sample. The results suggest that relatively more resources be spent on monitoring AFB₁/M₁ when both chemicals’ contamination fractions are low; when both contamination fractions are higher, relatively more budget should be addressed to monitoring dioxins.     

Thyroid Cancer Risk from Exposure to Ionizing Radiation: A Case Study in the Comparative Potency Model

Considerable controversy exists about the relative risk of thyroid cancer following exposure to external radiation compared to the risk after exposure to internally deposited 131I. The human epidemiological data are equivocal, and studies are not directly comparable owing to differing ages at exposure, dose ranges, and periods of follow-up. Limited experimental data at low dose ranges support the hypothesis of equal potency in animals. This report utilizes a relative potency model to reconcile data from different sources, and to provide an estimate of thyroid cancer risk following human exposure to 131I. We utilize data from epidemiological studies of external radiation and 131I exposure in humans and data from an experimental animal study. This analysis shows that the data provide no compelling evidence to suggest that the risks accompanying external radiation or 131I exposure are different.     

Assessment of Instructions on Protection Against Food Contaminated with Radiocesium in Japan in 2011

The Japan Ministry of Health, Labour and Welfare (MHLW) has published instructions for radiological protection against food after the Fukushima Daiichi nuclear power plant accident in 2011. Following the instructions, the export and consumption of food items identified as being contaminated were restricted for a certain period. We assessed the validity of the imposed restriction periods for two representative vegetables (spinach and cabbage) grown in Fukushima Prefecture from two perspectives: effectiveness for reducing dietary dose and economic efficiency. To assess effectiveness, we estimated the restriction period required to maintain consumers’ dose below the guidance dose levels. To assess economic efficiency, we estimated the restriction period that maximizes the net benefit to taxpayers. All estimated restriction periods were shorter than the actual restriction periods imposed on spinach and cabbage from Fukushima in 2011, which indicates that the food restriction effectively maintained consumers’ dietary dose below the guidance dose level, but in an economically inefficient manner. We also evaluated the response of the restriction period to the sample size for each weekly food safety test and the instructions for when to remove the restriction. Stringent MHLW instructions seemed to sufficiently reduce consumers’ health risk even when the sample size for the weekly food safety test was small, but tended to increase the economic cost to taxpayers.     

The Cancer Risk Associated with Residential Exposure to Soil Containing Radioactive Coal Combustion Residuals

Coal combustion residuals (CCRs) are composed of various constituents, including radioactive materials. The objective of this study was to utilize methodology on radionuclide risk assessment from the Environmental Protection Agency (EPA) to estimate the potential cancer risks associated with residential exposure to CCR‐containing soil. We evaluated potential radionuclide exposure via soil ingestion, inhalation of soil particulates, and external exposure to ionizing radiation using published CCR radioactivity values for ²³²Th, ²²⁸Ra, ²³⁸U, and ²²⁶Ra from the Appalachia, Illinois, and Powder River coal basins. Mean and upper‐bound cancer risks were estimated individually for each radionuclide, exposure pathway, and coal basin. For each radionuclide at each coal basin, external exposure to ionizing radiation contributed the greatest to the overall risk estimate, followed by incidental ingestion of soil and inhalation of soil particulates. The mean cancer risks by route of exposure were 2.01 × 10⁻⁶ (ingestion), 6.80 × 10⁻⁹ (inhalation), and 3.66 × 10⁻⁵ (external), while the upper bound cancer risks were 3.70 × 10⁻⁶ (ingestion), 1.18 × 10⁻⁸ (inhalation), and 6.15 × 10⁻⁵ (external), using summed radionuclide‐specific data from all locations. The upper bound cancer risk from all routes of exposure was 6.52 × 10⁻⁵. These estimated cancer risks were within the EPA's acceptable cancer risk range of 1 × 10⁻⁶ to 1 × 10⁻⁴. If the CCR radioactivity values used in this analysis are generally representative of CCR waste streams, then our findings suggest that CCRs would not be expected to pose a significant radiological risk to residents living in areas where contact with CCR‐containing soils might occur.     

Assessing Risk‐Based Upper Limits of Melamine Migration from Food Containers

Melamine contamination of food has become a major food safety issue because of incidents of infant disease caused by exposure to this chemical. This study was aimed at establishing a safety limit in Taiwan for the degree of melamine migration from food containers. Health risk assessment was performed for three exposure groups (preschool children, individuals who dine out, and elderly residents of nursing homes). Selected values of tolerable daily intake (TDI) for melamine were used to calculate the reference migration concentration limit (RMCL) or reference specific migration limit (RSML) for melamine food containers. The only existing values of these limits for international standards today are 1.2 mg/L (0.2 mg/dm²) in China and 30 mg/L (5 mg/dm²) in the European Union. The factors used in the calculations included the specific surface area of food containers, daily food consumption rate, body weight, TDI, and the percentile of the population protected at a given migration concentration limit (MCL). The results indicate that children are indeed at higher risk of melamine exposure at toxic levels than are other groups and that the 95th percentile of MCL (specific surface area = 5) for children aged 1–6 years should be the RMCL (0.07 mg/dm²) for protecting the sensitive and general population.     

A Multifactorial Risk Prioritization Framework for Foodborne Pathogens

We develop a prioritization framework for foodborne risks that considers public health impact as well as three other factors (market impact, consumer risk acceptance and perception, and social sensitivity). Canadian case studies are presented for six pathogen‐food combinations: Campylobacter spp. in chicken; Salmonella spp. in chicken and spinach; Escherichia coli O157 in spinach and beef; and Listeria monocytogenes in ready‐to‐eat meats. Public health impact is measured by disability‐adjusted life years and the cost of illness. Market impact is quantified by the economic importance of the domestic market. Likert‐type scales are used to capture consumer perception and acceptance of risk and social sensitivity to impacts on vulnerable consumer groups and industries. Risk ranking is facilitated through the development of a knowledge database presented in the format of info cards and the use of multicriteria decision analysis (MCDA) to aggregate the four factors. Three scenarios representing different stakeholders illustrate the use of MCDA to arrive at rankings of pathogen‐food combinations that reflect different criteria weights. The framework provides a flexible instrument to support policymakers in complex risk prioritization decision making when different stakeholder groups are involved and when multiple pathogen‐food combinations are compared.     

Development of a Unit Risk Factor for 1,3-Butadiene Based on an Updated Carcinogenic Toxicity Assessment

The Texas Commission on Environmental Quality (TCEQ) has developed an inhalation unit risk factor (URF) for 1,3-butadiene based on leukemia mortality in an updated epidemiological study on styrene-butadiene rubber production workers conducted by researchers at the University of Alabama at Birmingham. Exposure estimates were updated and an exposure estimate validation study as well as dose-response modeling were conducted by these researchers. This information was not available to the U.S. Environmental Protection Agency when it prepared its health assessment of 1,3-butadiene in 2002. An extensive analysis conducted by TCEQ discusses dose-response modeling, estimating risk for the general population from occupational workers, estimating risk for potentially sensitive subpopulations, effect of occupational exposure estimation error, and use of mortality rates to predict incidence. The URF is 5.0 × 10⁻⁷ per μg/m³ or 1.1 × 10⁻⁶ per ppb and is based on a Cox regression dose-response model using restricted continuous data with age as a covariate, and a linear low-dose extrapolation default approach using the 95% lower confidence limit as the point of departure. Age-dependent adjustment factors were applied to account for possible increased susceptibility for early life exposure. The air concentration at 1 in 100,000 excess leukemia mortality, the no-significant-risk level, is 20 μg/m³ (9.1 ppb), which is slightly lower than the TCEQ chronic reference value of 33 μg/m³ (15 ppb) protective of ovarian atrophy. These values will be used to evaluate ambient air monitoring data so the general public is protected against adverse health effects from chronic exposure to 1,3-butadiene.     

Lung Cancer Risk from Radon in Marcellus Shale Gas in Northeast U.S. Homes

The amount of radon in natural gas varies with its source. Little has been published about the radon from shale gas to date, making estimates of its impact on radon‐induced lung cancer speculative. We measured radon in natural gas pipelines carrying gas from the Marcellus Shale in Pennsylvania and West Virginia. Radon concentrations ranged from 1,520 to 2,750 Bq/m³ (41–74 pCi/L), and the throughput‐weighted average was 1,983 Bq/m³ (54 pCi/L). Potential radon exposure due to the use of Marcellus Shale gas for cooking and space heating using vent‐free heaters or gas ranges in northeastern U.S. homes and apartments was assessed. Though the measured radon concentrations are higher than what has been previously reported, it is unlikely that exposure from natural gas cooking would exceed 1.2 Bq/m³ (<1% of the U.S. Environmental Protection Agency's action level). Using worst‐case assumptions, we estimate the excess lifetime (70 years) lung cancer risk associated with cooking to be 1.8×10^?4 (interval spanning 95% of simulation results: 8.5×10^?5, 3.4×10^?4). The risk profile for supplemental heating with unvented gas appliances is similar. Individuals using unvented gas appliances to provide primary heating may face lifetime risks as high as 3.9×10^?3. Under current housing stock and gas consumption assumptions, expected levels of residential radon exposure due to unvented combustion of Marcellus Shale natural gas in the Northeast United States do not result in a detectable change in the lung cancer death rates.     

Optimal Inspection of Imports to Prevent Invasive Pest Introduction

The United States imports more than 1 billion live plants annually—an important and growing pathway for introduction of damaging nonnative invertebrates and pathogens. Inspection of imports is one safeguard for reducing pest introductions, but capacity constraints limit inspection effort. We develop an optimal sampling strategy to minimize the costs of pest introductions from trade by posing inspection as an acceptance sampling problem that incorporates key features of the decision context, including (i) simultaneous inspection of many heterogeneous lots, (ii) a lot‐specific sampling effort, (iii) a budget constraint that limits total inspection effort, (iv) inspection error, and (v) an objective of minimizing cost from accepted defective units. We derive a formula for expected number of accepted infested units (expected slippage) given lot size, sample size, infestation rate, and detection rate, and we formulate and analyze the inspector's optimization problem of allocating a sampling budget among incoming lots to minimize the cost of slippage. We conduct an empirical analysis of live plant inspection, including estimation of plant infestation rates from historical data, and find that inspections optimally target the largest lots with the highest plant infestation rates, leaving some lots unsampled. We also consider that USDA‐APHIS, which administers inspections, may want to continue inspecting all lots at a baseline level; we find that allocating any additional capacity, beyond a comprehensive baseline inspection, to the largest lots with the highest infestation rates allows inspectors to meet the dual goals of minimizing the costs of slippage and maintaining baseline sampling without substantial compromise.     

Risk Assessment of Human Listeriosis from Semisoft Cheeses Made from Raw Sheep's Milk in Lazio and Tuscany (Italy)

Semisoft cheese made from raw sheep's milk is traditionally and economically important in southern Europe. However, raw milk cheese is also a known vehicle of human listeriosis and contamination of sheep cheese with Listeria monocytogenes has been reported. In the present study, we have developed and applied a quantitative risk assessment model, based on available evidence and challenge testing, to estimate risk of invasive listeriosis due to consumption of an artisanal sheep cheese made with raw milk collected from a single flock in central Italy. In the model, contamination of milk may originate from the farm environment or from mastitic animals, with potential growth of the pathogen in bulk milk and during cheese ripening. Based on the 48‐day challenge test of a local semisoft raw sheep's milk cheese we found limited growth only during the initial phase of ripening (24 hours) and no growth or limited decline during the following ripening period. In our simulation, in the baseline scenario, 2.2% of cheese servings are estimated to have at least 1 colony forming unit (CFU) per gram. Of these, 15.1% would be above the current E.U. limit of 100 CFU/g (5.2% would exceed 1,000 CFU/g). Risk of invasive listeriosis per random serving is estimated in the 10^?12 range (mean) for healthy adults, and in the 10^?10 range (mean) for vulnerable populations. When small flocks (10–36 animals) are combined with the presence of a sheep with undetected subclinical mastitis, risk of listeriosis increases and such flocks may represent a public health risk.     

The Impact of Consumer Phase Models in Microbial Risk Analysis

In quantitative microbiological risk assessment (QMRA), the consumer phase model (CPM) describes the part of the food chain between purchase of the food product at retail and exposure. Construction of a CPM is complicated by the large variation in consumer food handling practices and a limited availability of data. Therefore, several subjective (simplifying) assumptions have to be made when a CPM is constructed, but with a single CPM their impact on the QMRA results is unclear. We therefore compared the performance of eight published CPMs for Campylobacter in broiler meat in an example of a QMRA, where all the CPMs were analyzed using one single input distribution of concentrations at retail, and the same dose‐response relationship. It was found that, between CPMs, there may be a considerable difference in the estimated probability of illness per serving. However, the estimated relative risk reductions are less different for scenarios modeling the implementation of control measures. For control measures affecting the Campylobacter prevalence, the relative risk is proportional irrespective of the CPM used. However, for control measures affecting the concentration the CPMs show some difference in the estimated relative risk. This difference is largest for scenarios where the aim is to remove the highly contaminated portion from human exposure. Given these results, we conclude that for many purposes it is not necessary to develop a new detailed CPM for each new QMRA. However, more observational data on consumer food handling practices and their impact on microbial transfer and survival are needed to generalize this conclusion.     

Health Risk Assessment of a Modern Municipal Waste Incinerator

During the modernization of the municipal waste incinerator (MWI, maximum capacity of 180,000 tons per year) of Metropolitan Grenoble (405,000 inhabitants), in France, a risk assessment was conducted, based on four tracer pollutants: two volatile organic compounds (benzene and 1, 1, 1 trichloroethane) and two heavy metals (nickel and cadmium, measured in particles). A Gaussian plume dispersion model, applied to maximum emissions measured at the MWI stacks, was used to estimate the distribution of these pollutants in the atmosphere throughout the metropolitan area. A random sample telephone survey (570 subjects) gathered data on time-activity patterns, according to demographic characteristics of the population. Life-long exposure was assessed as a time-weighted average of ambient air concentrations. Inhalation alone was considered because, in the Grenoble urban setting, other routes of exposure are not likely. A Monte Carlo simulation was used to describe probability distributions of exposures and risks. The median of the life-long personal exposures distribution to MWI benzene was 3.2·10^–5 g/m³ (20th and 80th percentiles = 1.5·10^–5 and 6.5·10^–5 g/m³), yielding a 2.6·10^–10 carcinogenic risk (1.2·10^–10–5.4·10^–10). For nickel, the corresponding life-time exposure and cancer risk were 1.8·10^–4 g/m³ (0.9.10^–4 – 3.6·10^–4 g/m³) and 8.6·10^–8 (4.3·10^–8–17.3·10^–8); for cadmium they were respectively 8.3·10^–6 g/m³ (4.0·10^–6–17.6·10^–6) and 1.5·10^–8 (7.2·10^–9–3.1·10^–8). Inhalation exposure to cadmium emitted by the MWI represented less than 1% of the WHO Air Quality Guideline (5 ng/m³), while there was a margin of exposure of more than 10⁹ between the NOAEL (150 ppm) and exposure estimates to trichloroethane. Neither dioxins nor mercury, a volatile metal, were measured. This could lessen the attributable life-long risks estimated. The minute (VOCs and cadmium) to moderate (nickel) exposure and risk estimates are in accord with other studies on modern MWIs meeting recent emission regulations, however.     

Validation of Quantitative Microbial Risk Assessment Using Epidemiological Data from Outbreaks of Waterborne Gastrointestinal Disease

The assumptions underlying quantitative microbial risk assessment (QMRA) are simple and biologically plausible, but QMRA predictions have never been validated for many pathogens. The objective of this study was to validate QMRA predictions against epidemiological measurements from outbreaks of waterborne gastrointestinal disease. I screened 2,000 papers and identified 12 outbreaks with the necessary data: disease rates measured using epidemiological methods and pathogen concentrations measured in the source water. Eight of the 12 outbreaks were caused by Cryptosporidium, three by Giardia, and one by norovirus. Disease rates varied from 5.5 × 10^?6 to 1.1 × 10^?2 cases/person‐day, and reported pathogen concentrations varied from 1.2 × 10^?4 to 8.6 × 10² per liter. I used these concentrations with single‐hit dose–response models for all three pathogens to conduct QMRA, producing both point and interval predictions of disease rates for each outbreak. Comparison of QMRA predictions to epidemiological measurements showed good agreement; interval predictions contained measured disease rates for 9 of 12 outbreaks, with point predictions off by factors of 1.0–120 (median = 4.8). Furthermore, 11 outbreaks occurred at mean doses of less than 1 pathogen per exposure. Measured disease rates for these outbreaks were clearly consistent with a single‐hit model, and not with a “two‐hit” threshold model. These results demonstrate the validity of QMRA for predicting disease rates due to Cryptosporidium and Giardia.     

Assessing Risk Factors in the Organic Control System: Evidence from Inspection Data in Italy

Certification is an essential feature in organic farming, and it is based on inspections to verify compliance with respect to European Council Regulation—EC Reg. No 834/2007. A risk‐based approach to noncompliance that alerts the control bodies to activate planning inspections would contribute to a more efficient and cost‐effective certification system. An analysis of factors that can affect the probability of noncompliance in organic farming has thus been developed. This article examines the application of zero‐inflated count data models to farm‐level panel data from inspection results and sanctions obtained from the Ethical and Environmental Certification Institute, one of the main control bodies in Italy. We tested many a priori hypotheses related to the risk of noncompliance. We find evidence of an important role for past noncompliant behavior in predicting future noncompliance, while farm size and the occurrence of livestock also have roles in an increased probability of noncompliance. We conclude the article proposing that an efficient risk‐based inspection system should be designed, weighting up the known probability of occurrence of a given noncompliance according to the severity of its impact.     

Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

Phthalate Exposure Through Food and Consumers' Risk Perception of Chemicals in Food

Phthalates have been detected in various types of retail foods. Consumers' exposure to phthalates is common. Consumers are concerned about chemicals in food. Our aim was to investigate the relationships between consumers' exposure to phthalates through food, consumers' interest in a natural and healthy diet, risk perception of food chemicals, and consumers' diet patterns. We collected data through a mail survey in the adult Swiss-German population ( N  = 1,200). We modeled exposure to di(2-ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP), benzyl butyl phthalate (BBP), and diethyl phthalate (DEP) based on a food frequency questionnaire and phthalate concentrations reported from food surveys. Using rating scales, we assessed risk perceptions of chemicals in food and interest in a natural and healthy diet. Higher risk perceptions and higher natural and healthy diet interest were associated with higher daily doses of DEHP, BBP, and DEP. No health risk from phthalates in food was identified for the vast majority of the population. Four consumers' diet clusters were discerned, with differences in phthalate exposure, risk perceptions, and interest in a natural and healthy diet. This study shows that even those consumers who express strong interest in natural food and low acceptance of food chemicals, and who try to make respective food choices, are exposed to contaminants such as phthalates.     

Risk ranking of food categories associated with Salmonella enterica contamination in the central region of Mexico

To prevent and control foodborne diseases, there is a fundamental need to identify the foods that are most likely to cause illness. The goal of this study was to rank 25 commonly consumed food products associated with Salmonella enterica contamination in the Central Region of Mexico. A multicriteria decision analysis (MCDA) framework was developed to obtain an S. enterica risk score for each food product based on four criteria: probability of exposure to S. enterica through domestic food consumption (Se); S. enterica growth potential during home storage (Sg); per capita consumption (Pcc); and food attribution of S. enterica outbreak (So). Risk scores were calculated by the equation Se*W₁+Sg*W₂+Pcc*W₃+So*W₄, where each criterion was assigned a normalized value (1–5) and the relative weights (W) were defined by 22 experts’ opinion. Se had the largest effect on the risk score being the criterion with the highest weight (35%; IC95% 20%–60%), followed by So (24%; 5%–50%), Sg (23%; 10%–40%), and Pcc (18%; 10%–35%). The results identified chicken (4.4 ± 0.6), pork (4.2 ± 0.6), and beef (4.2 ± 0.5) as the highest risk foods, followed by seed fruits (3.6 ± 0.5), tropical fruits (3.4 ± 0.4), and dried fruits and nuts (3.4 ± 0.5), while the food products with the lowest risk were yogurt (2.1 ± 0.3), chorizo (2.1 ± 0.4), and cream (2.0 ± 0.3). Approaches with expert-based weighting and equal weighting showed good correlation (R² = 0.96) and did not show significant differences among the ranking order in the top 20 tier. This study can help risk managers select interventions and develop targeted surveillance programs against S. enterica in high-risk food products.     

A Risk Assessment Model for Enterotoxigenic Staphylococcus aureus in Pasteurized Milk: A Potential Route to Source‐Level Inference

This article describes a probabilistic model that quantifies hazards that arise from Staphylococcus aureus in milk that is sold as pasteurized in the United Kingdom. The model is centered on coupled dynamics for S. aureus populations, staphylococcal enterotoxins, and the concentration of alkaline phosphatase throughout the milk chain. The chain includes farm collection and storage of pooled milk, further pooling for off‐farm processing, high temperature short time thermal processing, and possible postprocess contamination. The model is implemented as a Bayesian belief network. The results indicate that milk sold as pasteurized is relatively safe with respect to the hazards associated with S. aureus and that most risk is associated with small scale on‐farm processing. An additional analysis of likelihood ratios shows that alkaline phosphatase concentrations in filler tank milk are a good indicator of potential hazards and that these concentrations, in conjunction with other measurements, can be used effectively to discriminate over possible failure modes. The ability to discriminate over potential failure modes can support preemptive actions, such as maintenance or hygiene, which assist with milk chain management and, over extended periods, accumulate to drive improved safety, efficiency, and security.     

The Benefits of Probabilistic Exposure Assessment: Three Case Studies Involving Contaminated Air,Water, and Soil1

Probabilistic risk assessments are enjoying increasing popularity as a tool to characterize the health hazards associated with exposure to chemicals in the environment. Because probabilistic analyses provide much more information to the risk manager than standard “point” risk estimates, this approach has generally been heralded as one which could significantly improve the conduct of health risk assessments. The primary obstacles to replacing point estimates with probabilistic techniques include a general lack of familiarity with the approach and a lack of regulatory policy and guidance. This paper discusses some of the advantages and disadvantages of the point estimate vs. probabilistic approach. Three case studies are presented which contrast and compare the results of each. The first addresses the risks associated with household exposure to volatile chemicals in tapwater. The second evaluates airborne dioxin emissions which can enter the food-chain. The third illustrates how to derive health-based cleanup levels for dioxin in soil. It is shown that, based on the results of Monte Carlo analyses of probability density functions (PDFs), the point estimate approach required by most regulatory agencies will nearly always overpredict the risk for the 95^th percentile person by a factor of up to 5. When the assessment requires consideration of 10 or more exposure variables, the point estimate approach will often predict risks representative of the 99.9^th percentile person rather than the 50^th or 95^th percentile person. This paper recommends a number of data distributions for various exposure variables that we believe are now sufficiently well understood to be used with confidence in most exposure assessments. A list of exposure variables that may require additional research before adequate data distributions can be developed are also discussed.     

A Risk Assessment Framework for Assessing Metallic Nanomaterials of Environmental Concern: Aquatic Exposure and Behavior

Nanomaterials are finding application in many different environmentally relevant products and processes due to enhanced catalytic, antimicrobial, and oxidative properties of materials at this scale. As the market share of nano‐functionalized products increases, so too does the potential for environmental exposure and contamination. This study presents some exposure ranking methods that consider potential metallic nanomaterial surface water exposure and fate, due to nano‐functionalized products, through a number of exposure pathways. These methods take into account the limited and disparate data currently available for metallic nanomaterials and apply variability and uncertainty principles, together with qualitative risk assessment principles, to develop a scientific ranking. Three exposure scenarios with three different nanomaterials were considered to demonstrate these assessment methods: photo‐catalytic exterior paint (nano‐scale TiO₂), antimicrobial food packaging (nano‐scale Ag), and particulate‐reducing diesel fuel additives (nano‐scale CeO₂). Data and hypotheses from literature relating to metallic nanomaterial aquatic behavior (including the behavior of materials that may relate to nanomaterials in aquatic environments, e.g., metals, pesticides, surfactants) were used together with commercial nanomaterial characteristics and Irish natural aquatic environment characteristics to rank the potential concentrations, transport, and persistence behaviors within subjective categories. These methods, and the applied scenarios, reveal where data critical to estimating exposure and risk are lacking. As research into the behavior of metallic nanomaterials in different environments emerges, the influence of material and environmental characteristics on nanomaterial behavior within these exposure‐ and risk‐ranking methods may be redefined on a quantitative basis.