A Perspective on Dioxin Emissions from Municipal Solid Waste Incinerators

This paper discusses the following key issues concerning human exposure to dioxins and furans emitted from typical, modern MSW incinerators: (1) Are MSW incinerators the major source of PCDD/PCDF input into the environment? (2) Are environmental concentrations around MSW incinerators substantially elevated relative to background levels? And (3) are MSW incinerators the major source of human exposure to PCDDs and PCDFs? Current scientific evidence indicates that (1) combustion sources in general (including steel mills, copper smelting plants, motor vehicles, pulp and paper mills, and MSW incinerators) are major sources of PCDD/PCDF input in the environment; (2) environmental concentrations of PCDDs and PCDFs around operating MSW incinerators are not substantially elevated; and (3) 99% of human exposure to PCDDs and PCDFs is from background contamination, even for individuals living near a modern MSW incinerator.     

Infant Exposure Assessment for Breast Milk Dioxins and Furans Derived from Waste Incineration Emissions

Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) have been detected in human milk samples obtained in several countries. Possible sources include emissions from incineration of municipal waste in resource recovery facilities. A formula is presented for calculating the infant daily dose of dioxin equivalents from breast milk on the basis of the maternal daily intake. Application of the formula suggests that an infant breast-fed for 12 months would receive around 10% of the cumulative exposure dose per body weight that would be received by an adult with 50 years of exposure. Further analysis indicated that the contribution of dioxin equivalents from breast milk to an infant's body concentration at the end of 12 months of breast feeding would amount to 1.7 times the concentration in the mother. However, dioxin and furan emissions from a source calculated to result in worst-case lifetime cancer risks of the order of 1 in 100,000 are only likely to increase breast milk concentrations by around 1%-10% of the levels that have been detected in several countries. This finding suggests that there are major sources of dioxins and furans other than from municipal solid waste incineration that need to be identified.     

Meta-Analysis of Food Safety Information Based on a Combination of a Relational Database and a Predictive Modeling Tool

The management of microbial risk in food products requires the ability to predict growth kinetics of pathogenic microorganisms in the event of contamination and growth initiation. Useful data for assessing these issues may be found in the literature or from experimental results. However, the large number and variety of data make further development difficult. Statistical techniques, such as meta-analysis, are then useful to realize synthesis of a set of distinct but similar experiences. Moreover, predictive modeling tools can be employed to complete the analysis and help the food safety manager to interpret the data. In this article, a protocol to perform a meta-analysis of the outcome of a relational database, associated with quantitative microbiology models, is presented. The methodology is illustrated with the effect of temperature on pathogenic Escherichia coli and Listeria monocytogenes, growing in culture medium, beef meat, and milk products. Using a database and predictive models, simulations of growth in a given product subjected to various temperature scenarios can be produced. It is then possible to compare food products for a given microorganism, according to its growth ability in these products, and to compare the behavior of bacteria in a given foodstuff. These results can assist decisions for a variety of questions on food safety.     

Decision support for risks managers in the case of deliberate food contamination: The dairy industry as an example

Dairy farms were identified, which can be included in a contingency plan set up to prevent or mitigate the consequences of deliberate contamination of a food supply chain. The deliberate introduction of a contamination into the supply chain of milk was simulated in a scenario where milk producers serve as the entry sources and consumers of milk represent the target to be affected by the contamination. It is shown that the entry sources have an impact on the damage caused, i.e. in terms of the number of consumers reached. A contingency plan is provided that contains a list of entry sources ranked according to their impact on the damage to consumers. To generate this list, a computer program was developed that simulates the impact of the contaminations on consumers via the trade of contaminated milk. Possible variations in the trade links between milk producers, dairies and consumers as well as between dairies are considered. It is investigated how these trade links alter the generated list of entry sources.The results indicate that, regardless of the actual milk trade flow, control measures should be introduced on 39% of the milk producers in order to minimize the damage. The identification of suitable entry sources may help risk managers to focus on these farms in a contingency plan that improves the sensitivity of control activities related to deliberate contamination.     

基于消费者主权的生鲜电商消费体验设置

针对消费者对国内生鲜农产品质量安全的"信任危机",本文构建了植入消费体验的生鲜电商C2B2B2C模型,让碎片化的消费者通过互联网就近聚合为社群化的食物社区,生产者通过合作社聚合为规模化生产基地,食物社区与生产基地借助电商平台进行产销对接、以销定产和消费体验。研究表明,在传统B2C模式下消费者只能依据供应商提供的信息进行Stackelberg博弈和有限消费体验,购买需求较少。当植入充分的消费体验后,生产者与消费者融合为prosumer,购买需求随消费者对生产者的信任度增加而增加。实证揭示,农耕生产、质量追溯、物流配送、网购操作、产品呈现和售后服务都会显著影响消费体验,电商平台要实现商业可持续性发展必须为消费者设置这些全面而丰富的体验场景。     

Risks of Municipal Solid Waste Incineration: An Environmental Perspective

The central focus of the debate over incineration of municipal solid waste (MSW) has shifted from its apparent management advantages to unresolved risk issues. This shift is a result of the lack of comprehensive consideration of risks associated with incineration. We discuss the need to expand incinerator risk assessment beyond the limited view of incinerators as stationary air pollution sources to encompass the following: other products of incineration, ash in particular, and pollutants other than dioxins, metals in particular; routes of exposure in addition to direct inhalation; health effects in addition to cancer; and the cumulative nature of exposure and health effects induced by many incinerator-associated pollutants. Rational MSW management planning requires that the limitations as well as advantages of incineration be recognized. Incineration is a waste-processing--not a waste disposal--technology, and its products pose substantial management and disposal problems of their own. Consideration of the nature of these products suggests that incineration is ill-suited to manage the municipal wastestream in its entirety. In particular, incineration greatly enhances the mobility and bioavailability of toxic metals present in MSW. These factors suggest that incineration must be viewed as only one component in an integrated MSW management system. The potential for source reduction, separation, and recycling to increase the safety and efficiency of incineration should be counted among their many benefits. Risk considerations dictate that alternatives to the use of toxic metals at the production stage also be examined in designing an effective, long-term MSW management strategy.     

The Impact of Social Amplification and Attenuation of Risk and the Public Reaction to Mad Cow Disease in Canada

Following the detection of bovine spongiform encephalopathy (BSE) in Canada, and subsequently in the United States, confidence in the safety of beef products remained high. Consumers actually increased their consumption of beef slightly after the news of an increased risk from mad cow disease, which has been interpreted as public support for beef farmers and confidence in government regulators. The Canadian public showed a markedly different reaction to the news of domestic BSE than the furious and panicked responses observed in the United Kingdom, Germany, and Japan. Using the social amplification of risk framework, we show that, while other countries displayed social amplification of risk, Canada experienced a social attenuation of risk. The attenuated reaction in Canada toward mad cow disease and increased human health risks from variant Creutzfeldt-Jakob disease (vCJD) was due to the social context at the time when BSE was discovered domestically. Mortality, morbidity, and psychosocial impacts resulting from other major events such as severe acute respiratory syndrome (SARS), West Nile virus (WNV), and the U.S.-Iraq war made the theoretical risks of BSE and vCJD a lower priority, reducing its concern as a risk issue.     

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.     

生鲜农产品供应链关系契约稳定性影响研究——以冷链设施补贴模式为视角

基于我国当前生鲜农产品供应链中产品价格、盟员关系不稳定,农户和消费者利益受损的现实,本文通过构建两种供应链组织模式下的利润模型,研究了关系契约对农产品生鲜度及供应链利润的影响,并探讨了其"自我执行"机制;分析不同组织模式下冷链设施补贴模式对关系契约稳定性的影响。研究表明,关系契约在提升农产品生鲜度及供应链利润方面有显著作用,但不能完全保证契约的稳定性;引入冷链设施虽在进一步提高生鲜度及利润方面有明显作用,但不同引入方式对关系契约稳定性影响较大,而选择恰当的冷链设施补贴模式("公司+合作社+农户"组织模式下政府对农业合作社的补贴)可提升农产品生鲜度及农户盈利水平,最终提升生鲜农产品供应链关系契约的稳定性。     

Risk Perception of the "Mad Cow Disease" in France: Determinants and Consequences

Since 1996, when bovine spongiform encephalopathy (BSE) was assessed as a possible human transmissible disease, a variant of Creutzfeldt-Jakob disease (vCJD), French people have entered into a long period of fear and avoidance of beef and bovine byproducts, which produced an unprecedented collapse in the beef market. This article deals with the perceived risk of the "mad cow disease" (MCD) in the French general population. Two surveys were conducted on a representative sample of the adult population, the first one in 2000 during the peak of the crisis and the second one 13 months later in a quieter period. The main assumption we made was that changes in beef consumption are strongly related to the perceived risk of MCD, which we defined as people's cognitive and affective responses to hazard. Our objective was to identify the determinants and consequences of this perceived risk and to compare them in different sociopolitical contexts. The results issued from a bivariate and multivariate analysis show that: (i) the distribution of most of the variables significantly related to the perceived risk identified in the first survey had changed in the second survey, in relation with the reduction of worry and the resumption of national beef consumption; (ii) the propensity for self-protection through avoiding or ceasing beef eating was more related to feelings of worry than to subjective vCJD risk assessments; and (iii) the main determinant of less avoidance to beef products was the preference for beef, a feeling identified prior to emergence of the risk of MCD, remaining unchanged in various contexts.     

Dose-Response Model for 13 Strains of Salmonella

Data from a human feeding trial with healthy men were used to develop a dose-response model for 13 strains of Salmonella and to determine the effects of strain variation on the shape of the dose-response curve. Dose-response data for individual strains were fit to a three-phase linear model to determine minimum, median, and maximum illness doses, which were used to define Pert distributions in a computer simulation model. Pert distributions for illness dose of individual strains were combined in an Excel spreadsheet using a discrete distribution to model strain prevalence. In addition, a discrete distribution was used to model dose groups and thus create a model that simulated human feeding trials. During simulation of the model with @Risk, an illness dose and a dose consumed were randomly assigned to each consumption event in the simulated feeding trial and if the illness dose was greater than the dose consumed then the model predicted no illness, otherwise the model predicted that an illness would occur. To verify the dose-response model predictions, the original feeding trial was simulated. The dose-response model predicted a median of 69 (range of 43-101) illnesses compared to 74 in the original trial. Thus, its predictions were in agreement with the data used to develop it. However, predictions of the model are only valid for eggnog, healthy men, and the strains and doses of Salmonella used to develop it. When multiple strains of Salmonella were simulated together, the predicted dose-response curves were irregular in shape. Thus, the sigmoid shape of dose-response curves in feeding trials with one strain of Salmonella may not accurately reflect dose response in naturally contaminated food where multiple strains may be present.     

A Modular Bayesian Salmonella Source Attribution Model for Sparse Data

Several statistical models for salmonella source attribution have been presented in the literature. However, these models have often been found to be sensitive to the model parameterization, as well as the specifics of the data set used. The Bayesian salmonella source attribution model presented here was developed to be generally applicable with small and sparse annual data sets obtained over several years. The full Bayesian model was modularized into three parts (an exposure model, a subtype distribution model, and an epidemiological model) in order to separately estimate unknown parameters in each module. The proposed model takes advantage of the consumption and overall salmonella prevalence of the studied sources, as well as bacteria typing results from adjacent years. The latter were used for a smoothed estimation of the annual relative proportions of different salmonella subtypes in each of the sources. The source‐specific effects and the salmonella subtype‐specific effects were included in the epidemiological model to describe the differences between sources and between subtypes in their ability to infect humans. The estimation of these parameters was based on data from multiple years. Finally, the model combines the total evidence from different modules to proportion human salmonellosis cases according to their sources. The model was applied to allocate reported human salmonellosis cases from the years 2008 to 2015 to eight food sources.     

Consumer Risk Perceptions Toward Agricultural Biotechnology, Self-Protection, and Food Demand: The Case of Milk in the United States

This study is an econometric systems approach to modeling the factors and linkages affecting risk perceptions toward agricultural biotechnology, self-protection actions, and food demand. This model is applied to milk in the United States, but it can be adapted to other products as well as other categories of risk perceptions. The contribution of this formulation is the ability to examine how explanatory factors influence risk perceptions and whether they translate into behavior and ultimately what impact this has on aggregate markets. Hadden's outrage factors on heightening risk perceptions are among the factors examined. In particular, the article examines the role of labeling as a means of permitting informed consent to mitigate outrage factors. The effects of attitudinal, economic, and demographic factors on risk perceptions are also explored, as well as the linkage between risk perceptions, consumer behavior, and food demand. Because risk perceptions and self-protection actions are categorical variables and demand is a continuous variable, the model is estimated as a two-stage mixed system with a covariance correction procedure suggested by Amemiya. The findings indicate that it is the availability of labeling, not the price difference, between that labeled milk and milk produced with recombinant bovine Somatotropin (rbST) that significantly affects consumer's selection of rbST-free milk. The results indicate that greater availability of labeled milk would not only significantly increase the proportion of consumers who purchased labeled milk, its availability would also reduce the perception of risk associated with rbST, whether consumers purchase it or not. In other words, availability of rbST-free milk translates into lower risk perceptions toward milk produced with rbST.     

A Bayesian Approach to Quantify the Contribution of Animal-Food Sources to Human Salmonellosis

Based on the data from the integrated Danish Salmonella surveillance in 1999, we developed a mathematical model for quantifying the contribution of each of the major animal-food sources to human salmonellosis. The model was set up to calculate the number of domestic and sporadic cases caused by different Salmonella sero and phage types as a function of the prevalence of these Salmonella types in the animal-food sources and the amount of food source consumed. A multiparameter prior accounting for the presumed but unknown differences between serotypes and food sources with respect to causing human salmonellosis was also included. The joint posterior distribution was estimated by fitting the model to the reported number of domestic and sporadic cases per Salmonella type in a Bayesian framework using Markov Chain Monte Carlo simulation. The number of domestic and sporadic cases was obtained by subtracting the estimated number of travel- and outbreak-associated cases from the total number of reported cases, i.e., the observed data. The most important food sources were found to be table eggs and domestically produced pork comprising 47.1% (95% credibility interval, CI: 43.3-50.8%) and 9% (95% CI: 7.8-10.4%) of the cases, respectively. Taken together, imported foods were estimated to account for 11.8% (95% CI: 5.0-19.0%) of the cases. Other food sources considered had only a minor impact, whereas 25% of the cases could not be associated with any source. This approach of quantifying the contribution of the various sources to human salmonellosis has proved to be a valuable tool in risk management in Denmark and provides an example of how to integrate quantitative risk assessment and zoonotic disease surveillance.     

Risk Assessment of Escherichia coli O157 Illness from Consumption of Hamburgers in the United States Made from Australian Manufacturing Beef

We analyze the risk of contracting illness due to the consumption in the United States of hamburgers contaminated with enterohemorrhagic Escherichia coli (EHEC) of serogroup O157 produced from manufacturing beef imported from Australia. We have used a novel approach for estimating risk by using the prevalence and concentration estimates of E. coli O157 in lots of beef that were withdrawn from the export chain following detection of the pathogen. For the purpose of the present assessment an assumption was that no product is removed from the supply chain following testing. This, together with a number of additional conservative assumptions, leads to an overestimation of E. coli O157‐associated illness attributable to the consumption of ground beef patties manufactured only from Australian beef. We predict 49.6 illnesses (95%: 0.0–148.6) from the 2.46 billion hamburgers made from 155,000 t of Australian manufacturing beef exported to the United States in 2012. All these illness were due to undercooking in the home and less than one illness is predicted from consumption of hamburgers cooked to a temperature of 68 °C in quick‐service restaurants.     

Combining Quantitative Risk Assessment of Human Health,Food Waste,and Energy Consumption: The Next Step in the Development of the Food Cold Chain?

The preservation of perishable food via refrigeration in the supply chain is essential to extend shelf life and provide consumers with safe food. However, electricity consumed in refrigeration processes has an economical and an environmental impact. This study focuses on the cold chain of cooked ham, including transport, cold room in supermarket, display cabinet, transport by consumer, and domestic refrigerator, and aims to predict the risk for human health associated with Listeria monocytogenes, the amount of food wasted due to the growth of spoilage bacteria, and the electrical consumption to maintain product temperature through the cold chain. A set of eight intervention actions were tested to evaluate their impact on the three criteria. Results show that the modification of the thermostat of the domestic refrigerator has a high impact on food safety and food waste and a limited impact on the electrical consumption. Inversely, the modification of the airflow rate in the display cabinet has a high impact on electrical consumption and a limited impact on food safety and food waste. A cost–benefit analysis approach and two multicriteria decision analysis methods were used to rank the intervention actions. These three methodologies show that setting the thermostat of the domestic refrigerator to 4 °C presents the best compromise between the three criteria. The impact of decisionmaker preferences (criteria weight) and limitations of these three approaches are discussed. The approaches proposed by this study may be useful in decision making to evaluate global impact of intervention actions in issues involving conflicting outputs.     

Norovirus Dose–Response: Are Currently Available Data Informative Enough to Determine How Susceptible Humans Are to Infection from a Single Virus?

Two forms of single‐hit infection dose‐response models have previously been developed to assess available data from human feeding trials and estimate the norovirus dose‐response relationship. The mechanistic interpretations of these models include strong assumptions that warrant reconsideration: the first study includes an implicit assumption that there is no immunity to Norwalk virus among the specific study population, while the recent second study includes assumptions that such immunity could exist and that the nonimmune have no defensive barriers to prevent infection from exposure to just one virus. Both models addressed unmeasured virus aggregation in administered doses. In this work, the available data are reanalyzed using a generalization of the first model to explore these previous assumptions. It was hypothesized that concurrent estimation of an unmeasured degree of virus aggregation and important dose‐response parameters could lead to structural nonidentifiability of the model (i.e., that a diverse range of alternative mechanistic interpretations yield the same optimal fit), and this is demonstrated using the profile likelihood approach and by algebraic proof. It is also demonstrated that omission of an immunity parameter can artificially inflate the estimated degree of aggregation and falsely suggest high susceptibility among the nonimmune. The currently available data support the assumption of immunity within the specific study population, but provide only weak information about the degree of aggregation and susceptibility among the nonimmune. The probability of infection at low and moderate doses may be much lower than previously asserted, but more data from strategically designed dose‐response experiments are needed to provide adequate information.     

时间约束下不对称信息鲜活农产品供应链应对突发事件协调模型

针对一个由供应商和一个零售商构成的鲜活农产品供应链,在考虑损耗和新鲜度的影响下,假设产品的市场需求为零售价格的非线性函数,零售商成本为私有信息,研究如何协调供应链应对突发事件。 首先,给出了对称信息下供应链协调模型;然后,研究了不对称信息下集权式与分权式供应链的协调机制;再次,研究了在突发事件引起零售商成本分布函数扰动情况下,供应链的最优应对策略。 研究表明,供应链的最优生产计划、最优批发价格和最优零售价格均具有一定的鲁棒性,当突发事件造成零售商期望成本在一定范围内发生扰动时,三者可以保持不变。最后,通过数值仿真验证了相关结论。     

Bisphenol A: How the Most Relevant Exposure Sources Contribute to Total Consumer Exposure

Bisphenol A (BPA) is an endocrine disrupting chemical that is found in human urine throughout industrial societies around the globe. Consumer exposure pathways to BPA include packaged food, household dust, air, and dental fillings. To date, information on the relative contribution of the different pathways to total consumer exposure is lacking, but is key for managing substance‐associated risks. We investigated the relative contributions of the pathways known to be most relevant for nine different consumer groups. Our results suggest that the most important pathways for infants and children are the use of polycarbonate (PC) baby bottles and for adults and teenagers the consumption of canned food. Dental surgery can also considerably contribute over a short time directly after the surgery. For infants fed with PC baby bottles with mean dose rates of 0.8 μg/kg_bw/d the highest exposure dose rate was calculated. This dose rate is far below the tolerable daily intake of 50 μg/kg_bw/d. However, it is of the same order of magnitude as recently reported concentrations that caused low‐dose health effects in rodents. We find a pattern of falling exposure levels with rising age that is supported by urinary concentrations of BPA available for selected consumer groups. Similarly, the exposure levels we predict are confirmed by the levels reported in these studies.     

Bayesian Stacked Parametric Survival with Frailty Components and Interval‐Censored Failure Times: An Application to Food Allergy Risk

To better understand the risk of exposure to food allergens, food challenge studies are designed to slowly increase the dose of an allergen delivered to allergic individuals until an objective reaction occurs. These dose‐to‐failure studies are used to determine acceptable intake levels and are analyzed using parametric failure time models. Though these models can provide estimates of the survival curve and risk, their parametric form may misrepresent the survival function for doses of interest. Different models that describe the data similarly may produce different dose‐to‐failure estimates. Motivated by predictive inference, we developed a Bayesian approach to combine survival estimates based on posterior predictive stacking, where the weights are formed to maximize posterior predictive accuracy. The approach defines a model space that is much larger than traditional parametric failure time modeling approaches. In our case, we use the approach to include random effects accounting for frailty components. The methodology is investigated in simulation, and is used to estimate allergic population eliciting doses for multiple food allergens.