Genetically modified crops and aquatic ecosystems: considerations for environmental risk assessment and non-target organism testing

Environmental risk assessments (ERA) support regulatory decisions for the commercial cultivation of genetically modified (GM) crops. The ERA for terrestrial agroecosystems is well-developed, whereas guidance for ERA of GM crops in aquatic ecosystems is not as well-defined. The purpose of this document is to demonstrate how comprehensive problem formulation can be used to develop a conceptual model and to identify potential exposure pathways, using Bacillus thuringiensis (Bt) maize as a case study. Within problem formulation, the insecticidal trait, the crop, the receiving environment, and protection goals were characterized, and a conceptual model was developed to identify routes through which aquatic organisms may be exposed to insecticidal proteins in maize tissue. Following a tiered approach for exposure assessment, worst-case exposures were estimated using standardized models, and factors mitigating exposure were described. Based on exposure estimates, shredders were identified as the functional group most likely to be exposed to insecticidal proteins. However, even using worst-case assumptions, the exposure of shredders to Bt maize was low and studies supporting the current risk assessments were deemed adequate. Determining if early tier toxicity studies are necessary to inform the risk assessment for a specific GM crop should be done on a case by case basis, and should be guided by thorough problem formulation and exposure assessment. The processes used to develop the Bt maize case study are intended to serve as a model for performing risk assessments on future traits and crops.     

The Health Risk Assessment Performed in California for the Herbicide Simazine: A Case Study

Simazine, a member of the triazine group, is registered in California for weed control in soils where a wide range of crops will be (or are) planted. The health risks from simazine use in California were recently assessed by the California Department of Pesticide Regulation (CDPR) for all potential (acute and long-term) exposure scenarios relevant to Californian residents and workers. The results of the CDPR risk assessment indicate that current exposure levels in many of the scenarios under consideration are not health protective for the people in California. The main objective of the present summary report (i.e., case study) was two-fold, both for offering a forum to advance further scientific discussion: (1) to highlight the toxicity and exposure data as well as the assumptions used in the CDPR simazine risk assessment and then (2) to systematically requalify the uncertainties and complexities involved in terms of the toxicity and exposure appraisals given in that risk assessment. In both attempts, the focus was more on residential exposures for young children and women of child-bearing age in that simazine was reportedly seen to exhibit neuroendocrine effects across a variety of species.     

生态风险评价方法述评

生态风险是由环境的自然变化或人类活动引起的生态系统组成、结构的改变而导致系统功能损失的可能性。生态风险评价是定量预测各种风险源对生态系统产生风险的或然性以及评估该风险可接受程度的方法体系,因而是生态环境风险管理与决策的定量依据。在介绍了生态风险概念的基础上,按照风险源性质的分类标准将生态风险划分为化学污染类风险源、生态事件类风险源、复合类风险源3类,并分别论述了3类生态风险对应评价方法的特点与发展的方向。另外,针对生态风险评价研究的现状,讨论了我国生态风险研究的优先领域,包括建立急性、慢性毒理数据库,构建外来生物入侵风险评价标准等,同时,建议将综合概率统计学、复杂系统理论与遥感技术等手段引入生态风险评价方法中,以进一步提高风险评价结果在生态风险管理中的有效性。     

Mechanistic modeling of salmonellosis: Update and future directions

Microbial risk assessors often make simplifying assumptions that lead to the selection of simple concave functions with low-dose linearity, consistent with no-threshold and single-hit hypotheses, as default dose–response model forms. However, evidence is accumulating as the “microbiome revolution” progresses that challenge these assumptions that influence the estimates of the nature and magnitude of uncertainties associated with microbial risks. Scientific advances in the knowledge of the human “superorganism” (hybrid consortium of human plus microbial communities that cooperatively regulates health and disease) enable the design of definitive studies to estimate the pathogen doses overcome by the innate defenses, including the protective microbiota. The systematic investigation of the events of non-typhoid salmonellosis in humans undertaken nearly 2 decades ago was updated to incorporate recent scientific advances in the understanding of impact of the healthy superorganism that strengthens and extends the biological motivations for sublinear or convex dose–response curves in microbial risk assessment. The knowledge of colonization resistance (innate protection of the human superorganism from low doses of ingested pathogens) and microbiota-mediated clearance is advancing mechanistically for many pathosystems. However, until more detailed mechanistic data become available for salmonellosis, the consideration of a variety of empirical model forms is essential for depicting the uncertainty of the “true” dose–response model.     

Applying USEPA Risk Assessment Guidance in the 90s

Over the past decade, risk assessment has become increasingly relied upon for helping to make environmental management decisions. This trend has been accompanied by research and refinements in basic risk assessment methodologies to improve our ability to understand and evaluate the human health risks associated with chemical exposures.Despite this progress, significant uncertainties continue to be associated with the risk assessment process. These uncertainties typically derive from gaps in available data regarding chemical toxicity, and from difficulties in reliably estimating the magnitude of chemical exposures. Given these limitations, risk assessment is generally most valuable in evaluating relative risk; for example, when comparing alternatives to achieving a specified goal, setting priorities for protecting human health, or establishing procedures for properly allocating resources. Risk assessment can also be useful for developing regulatory benchmarks such as permit limits for air or water. In many cases, however, the limitations of the risk assessment process make it difficult (if not impossible) to reliably estimate an absolute level of risk, especially for a specific individual in an exposed population. In such cases, risk assessment can be seriously misapplied, and its results misinterpreted.This paper discusses some of the challenges that have been faced by the field of risk assessment during the 1990s. Current trends in risk assessment, and its use by regulatory agencies in making risk management decisions, are also described.     

Scientific data and theories for salmonellosis dose–response assessment

An “expansive” risk assessment approach is illustrated, characterizing dose–response relationships for salmonellosis in light of the full body of evidence for human and murine superorganisms. Risk assessments often require analysis of costs and benefits for supporting public health decisions. Decision-makers and the public need to understand uncertainty in such analyses for two reasons. Uncertainty analyses provide a range of possibilities within a framework of present scientific knowledge, thus helping to avoid undesirable consequences associated with the selected policies. And, it encourages the risk assessors to scrutinize all available data and models, thus helping avoid subjective or systematic errors. Without the full analysis of uncertainty, decisions could be biased by judgments based solely on default assumptions, beliefs, and statistical analyses of selected correlative data. Alternative data and theories that incorporate variability and heterogeneity for the human and murine superorganisms, particularly colonization resistance, are emerging as major influences for microbial risk assessment. Salmonellosis risk assessments are often based on conservative default models derived from selected sets of outbreak data that overestimate illness. Consequently, the full extent of uncertainty of estimates of annual number of illnesses is not incorporated in risk assessments and the presently used models may be incorrect.     

Non-target organism risk assessment of MIR604 maize expressing mCry3A for control of corn rootworm

Abstract:  Event MIR604 maize expresses a modified Cry3A protein (mCry3A), for control of corn rootworm. As part of the environmental safety assessment of MIR604 maize, risks to non-target organisms of mCry3A were assessed. The potential exposure of non-target organisms to mCry3A following cultivation of MIR604 maize was determined, and the hypothesis that such exposure is not harmful was tested. The hypothesis was tested rigorously by making worst-case or highly conservative assumptions about exposure, along with laboratory testing for hazards using species taxonomically related to the target pest and species expected to have high exposure to mCry3A, or both. Further rigour was introduced by study designs incorporating long exposures and measurements of sensitive endpoints. No adverse effects were observed in any study, and in most cases exposure to mCry3A in the study was higher than the worst-case expected exposure. In all cases, exposure in the study was higher than realistic, but still conservative, estimates of exposure. These results indicate minimal risk of MIR604 maize to non-target organisms.     

Acrylamide: a review of its genotoxicity and an assessment of heritable genetic risk

An updated review of the genotoxicity studies with acrylamide is provided. Then, using data from the studies generating quantitative information concerning heritability of genetic effects, an assessment of the heritable genetic risk presented by acrylamide is presented. The review offers a discussion of the reactions and possible mechanisms of genotoxic action by acrylamide and its epoxide metabolite glycidamide. Several genetic risk approaches are discussed, including the parallelogram, direct (actually a modified direct), and doubling dose approaches. Using data from the specific-locus and heritable translocation assays, the modified direct and doubling dose approaches are utilized to quantitate genetic risk. Exposures of male parents to acrylamide via inhalation, ingestion, and dermal routes are also quantitated. With these approaches and measurements and their underlying assumptions concerning extrapolation factors (including germ cell stage specificity, DNA repair variability, locus specificity), number of human loci associated with dominant disease alleles, and spontaneous mutation rates, an assessment of heritable genetic risk for humans is calculated for the three exposure scenarios. The calculated estimates for offspring from fathers exposed to acrylamide via drinking water are up to three offspring potentially affected with induced genetic disease per 10⁸ offspring. Estimates for inhalation or dermal exposures suggest higher risks for induced genetic disease in offspring from fathers exposed in occupational settings.     

Improving Risk Assessment: Toxicological Research Needs

A workshop convened to define research needs in toxicology identified several deficiencies in data and methods currently applied in risk assessment. The workshop panel noted that improving the link between chemical exposure and toxicological response requires a better understanding of the biological basis for inter-and intra-human variability and susceptibility. This understanding will not be complete unless all life stages are taken into consideration. Because animal studies serve as a foundation for toxicological assessment, proper accounting for cross-species extrapolation is essential. To achieve this, adjustments for dose-rate effects must be improved, which will aid in extrapolating toxicological responses to low doses and from short-term exposures. Success depends on greater use of validated biologically based dose-response models that include pharmacokinetic and pharmacodynamic data. Research in these areas will help define uncertainty factors and reduce reliance on underlying default assumptions. Throughout the workshop the panel recognized that biomedical science and toxicology in particular is on the verge of a revolution because of advances in genomics and proteomics. Data from these high-output technologies are anticipated to greatly improve risk assessment by enabling scientists to better define and model the elements of the relationship between exposure to biological hazards and health risks in populations with differing susceptibilities.     

Is Cancer in Israeli Professional Divers Exposed to Polluted Waters an Occupational Disease?

Because there is some contamination of practically every body of water, risk analysis is important to determine diving exposure standards to pollutants, including requirements for protective equipment. In the following study we attempt to determine the increased risk of cancer in Israeli Naval divers exposed to pollutants in the Kishon River system. We calculated two risks, one using maximally recorded levels of pollutants outside the diving areas (worst-case scenario), and the other using maximally recorded levels in the actual diving areas. For both calculations we used conservative assumptions for exposure (2500 exposure hours with 50% of body covered with sediment), and a synergistic risk model. We considered all chemicals that were carcinogenic by inhalation also to be carcinogenic by oral and dermal absorption. The relative risk was 1.13 for the worst-case scenario, and 1.004 for exposures in actual diving areas. We conclude that it is unlikely that exposure to the polluted Kishon River waters can cause a detectable increase in cancer risk in Israeli Navy divers. This study has implications for professional divers exposed to polluted waters.     

Probabilistic Analysis of Human Health Risks Associated with Background Concentrations of Inorganic Arsenic: Use of a Margin of Exposure Approach

Substantial evidence exists from epidemiological and mechanistic studies supporting a sublinear or threshold dose–response relationship for the carcinogenicity of ingested arsenic; nonetheless, current regulatory agency evaluations have quantified arsenic risks using default, generic risk assessment procedures that assume a linear, no-threshold dose–response relationship. The resulting slope factors predict risks from U.S. background arsenic exposures that exceed certain regulatory levels of concern, an outcome that presents challenges for risk communication and risk management decisions. To better reflect the available scientific evidence, this article presents the results of a Margin of Exposure (MOE) analysis to characterize risks associated with typical and high-end background exposures of the U.S. population to arsenic from food, water, and soil. MOE values were calculated by comparing a no-observable-adverse-effect-level (NOAEL) derived from the epidemiological literature with exposure estimates generated using a probabilistic (Monte Carlo) model. The plausibility and conservative nature of the exposure and risk estimates evaluated in this analysis are supported by sensitivity and uncertainty analyses and by comparing predicted urinary arsenic concentrations with empirical data. Using the more scientifically supported MOE approach, the analysis presented in this article indicates that typical and high-end background exposures to inorganic arsenic in U.S. populations do not present elevated risks of carcinogenicity.     

Carcinogenic risk assessment: some points of interest for a discussion

This paper is aimed at providing some elements of discussion about points that emerge about the meaning of risk assessment procedures. The considerations that will be developed mainly pertain to four topics. First, the feasibility of objectively checking the validity of risk assessment results on the basis of epidemiological data, particularly for very low exposures. Second, the influence of uncertainty factors and the resulting variations in risk estimates. Third, the influence of individual susceptibility factors, easily entailing differences in risk in the order of three levels of magnitude. These differences, as a consequence of genetic factors, are often in the range of three orders of negritude and are more evident for low classes of exposure. In the general population, DNA repair related susceptibility should also be considered. Fourth, the mathematical model of the risk assessment procedure may itself influence the results. The default approach adopted by the US EPA is commented.     

PestLCI 2.0: a second generation model for estimating emissions of pesticides from arable land in LCA

Purpose

The spatial dependency of pesticide emissions to air, surface water and groundwater is illustrated and quantified using PestLCI 2.0, an updated and expanded version of PestLCI 1.0.

Methods

PestLCI is a model capable of estimating pesticide emissions to air, surface water and groundwater for use in life cycle inventory (LCI) modelling of field applications. After calculating the primary distribution of pesticides between crop and soil, specific modules calculate the pesticide??s fate, thus determining the pesticide emission pattern for the application. PestLCI 2.0 was developed to overcome the limitations of the first model version, replacement of fate calculation equations and introducing new modules for macropore flow and effects of tillage. The accompanying pesticide database was expanded, the meteorological and soil databases were extended to include a range of European climatic zones and soil profiles. Environmental emissions calculated by PestLCI 2.0 were compared to results from the risk assessment models SWASH (surface water emissions), FOCUSPEARL (groundwater via matrix leaching) and MACRO (groundwater including macropore flow, only one scenario available) to partially validate the updated model. A case study was carried out to demonstrate the spatial variation of pesticide emission patterns due to dependency on meteorological and soil conditions.

Results

Compared to PestLCI 1.0, PestLCI 2.0 calculated lower emissions to surface water and higher emissions to groundwater. Both changes were expected due to new pesticide fate calculation approaches and the inclusion of macropore flow. Differences between the SWASH and FOCUSPEARL and PestLCI 2.0 emission estimates were generally lower than 2 orders of magnitude, with PestLCI generally calculating lower emissions. This is attributed to the LCA approach to quantify average cases, contrasting with the worst-case risk assessment approach inherent to risk assessment. Compared to MACRO, the PestLCI 2.0 estimates for emissions to groundwater were higher, suggesting that PestLCI 2.0 estimates of fractions leached to groundwater may be slightly conservative as a consequence of the chosen macropore modelling approach. The case study showed that the distribution of pesticide emissions between environmental compartments strongly depends on local climate and soil characteristics.

Conclusions

PestLCI 2.0 is partly validated in this paper. Judging from the validation data and case study, PestLCI 2.0 is a pesticide emission model in acceptable accordance with both state-of-the-art pesticide risk assessment models. The case study underlines that the common pesticide emission estimation practice in LCI may lead to misestimating the toxicity impacts of pesticide use in LCA.     

A Probabilistic Risk Assessment of the Effects of Methylmercury on Great Egrets and Bald Eagles Foraging at a Constructed Wetland in South Florida Relative to the Everglades

This case study summarizes an assessment of risk of methylmercury (MeHg) exposure to fish–eating birds foraging at Stormwater Treatment Area–2 (STA–2). This assessment was required as a special condition for a permit modification authorizing flow–through operation of STA–2 Cell 1 without it first satisfying formal mercury start–up criteria. The assessment estimates the risks posed by MeHg to the great egret (Ardea albus) and the bald eagle (Haliaeetus leucocephalus). Exposure models were based on literature–derived life history parameters combined with site–specific MeHg concentrations in water, sediment, and fish. To assess risk, daily MeHg intake by females and cumulative MeHg consumed by nestlings were compared to literature–derived effects thresholds. The results indicated the likelihood was low that MeHg exposures to birds foraging throughout STA–2 would exceed effects thresholds at the time of this assessment. Birds foraging exclusively from Cell 1 or the small discharge canal were predicted to experience greater exposures and could be at potential risk. However, this worst–case risk was comparable or lower than risk levels encountered in nearby water conservation areas or the Everglades National Park.     

Ecological Risk Assessment and the Precautionary Principle

The Precautionary Principle, generated during the late 1980s as a unifying principle for regulating discharge of hazardous material into the North Sea, has been broadened to include a shifting of the burden of proof to the proponent of a proposed activity, adoption of a more holistic assessment process, and encompassing all environmental management decisions, not just pollution prevention activities. We argue that the Precautionary Principle remains a management philosophy, not a substitute for risk assessment. Risk assessment is a tool for organizing information used in environmental management decisions. However, increasing attention to reducing the Type II error of risk assessment studies would significantly reduce the skepticism with which many view the risk assessment process. A critical review of default assumptions used in risk assessments, inclusion of indirect effects within an ecologically relevant spatial/temporal framework, and better communication between risk assessors and risk managers also would enhance the acceptability of the process. Risk assessment can provide a sound basis for management decisions regardless of the underlying philosophies of environmental conservation or utilitarianism, but only if the inherent biases in the risk assessment assumptions are acknowledged explicitly throughout the assessment and management processes.     

Plutonium worker dosimetry

Epidemiological studies of the relationship between risk and internal exposure to plutonium are clearly reliant on the dose estimates used. The International Commission on Radiological Protection (ICRP) is currently reviewing the latest scientific information available on biokinetic models and dosimetry, and it is likely that a number of changes to the existing models will be recommended. The effect of certain changes, particularly to the ICRP model of the respiratory tract, has been investigated for inhaled forms of ²³⁹Pu and uncertainties have also been assessed. Notable effects of possible changes to respiratory tract model assumptions are (1) a reduction in the absorbed dose to target cells in the airways, if changes under consideration are made to the slow clearing fraction and (2) a doubling of absorbed dose to the alveolar region for insoluble forms, if evidence of longer retention times is taken into account. An important factor influencing doses for moderately soluble forms of ²³⁹Pu is the extent of binding of dissolved plutonium to lung tissues and assumptions regarding the extent of binding in the airways. Uncertainty analyses have been performed with prior distributions chosen for application in epidemiological studies. The resulting distributions for dose per unit intake were lognormal with geometric standard deviations of 2.3 and 2.6 for nitrates and oxides, respectively. The wide ranges were due largely to consideration of results for a range of experimental data for the solubility of different forms of nitrate and oxides. The medians of these distributions were a factor of three times higher than calculated using current default ICRP parameter values. For nitrates, this was due to the assumption of a bound fraction, and for oxides due mainly to the assumption of slower alveolar clearance. This study highlights areas where more research is needed to reduce biokinetic uncertainties, including more accurate determination of particle transport rates and long-term dissolution for plutonium compounds, a re-evaluation of long-term binding of dissolved plutonium, and further consideration of modeling for plutonium absorbed to blood from the lungs.     

Comprehensive Realism's Weight-of-Evidence Based Distributional Dose-Response Characterization

Challenges to low-dose linearity and other default assumptions in cancer risk assessment and the limitations associated with NOAELs, LOAELs, and constant uncertainty factor values in the evaluation of noncancer health effects have stimulated the continued evolution of risk assessment methodologies. The increasing need for more realistic estimates of the dose-response relationship, better uncertainty characterization, and greater utilization of cost-benefit analyses have also contributed to this evolution. “Comprehensive Realism” is an emerging quantitative weight-of-evidence based risk assessment methodology for both cancer and noncancer health effects which utilizes probability distributions and decision analysis techniques to reflect more of the relevant human exposure data, more of the available and pertinent human and animal dose-response data, and the current state of knowledge about the relative plausibility of alternative dose-response analyses. A tree (like a decision tree and a probability tree) is used to decompose the dose-response assessment into component factors, to provide a structure for explicitly considering multiple alternatives for each factor, and to explicitly incorporate the current state of knowledge about the relative plausibility of these alternatives. Groundbreaking work has demonstrated the feasibility of weight-of-evidence based distributional characterizations, and provided initial examples. Computer software implementations are also available.     

The Use of Epidemiology in Risk Assessment: Challenges and Opportunities

The assessment of risk from environmental and occupational exposures incorporates and synthesizes data from a variety of scientific disciplines including toxicology and epidemiology. Epidemiological data have offered valuable contributions to the identification of human health hazards, estimation of human exposures, quantification of the exposure–response relation, and characterization of risks to specific target populations including sensitive populations. As with any scientific discipline, there are some uncertainties inherent in these data; however, the best human health risk assessments utilize all available information, characterizing strengths and limitations as appropriate. Human health risk assessors evaluating environmental and occupational exposures have raised concerns about the validity of using epidemiological data for risk assessment due to actual or perceived study limitations. This article highlights three concerns commonly raised during the development of human health risk assessments of environmental and occupational exposures: (a) error in the measurement of exposure, (b) potential confounding, and (c) the interpretation of non-linear or non-monotonic exposure–response data. These issues are often the content of scientific disagreement and debate among the human health risk assessment community, and we explore how these concerns may be contextualized, addressed, and often ameliorated.     

Production of fine and speciality chemicals: procedure for the estimation of LCIs

Goal, Scope, Background  To improve the environmental performance of chemical products or services, especially via comparisons of chemical products, LCA is a suitable evaluation method. However, no procedure to obtain comprehensive LCI-data on the production of fine and speciality chemicals is available to date, and information on such production processes is scarce. Thus, a procedure was developed for the estimation of LCIs of chemical production process-steps, which relies on only a small amount of input data. Methods  A generic input-output scheme of chemical production process-steps was set up, and equations to calculate inputs and outputs were established. For most parameters in the resulting estimation procedure, default values were derived from on-site data on chemical production processes and from heuristics. Uncertainties in the estimated default values were reflected as best-case and worst-case scenarios. The procedure was applied to a case study comparing the production of two active ingredients used for crop protection. Verification and a sensitivity analysis were carried out. Results and Discussion  It was found that the impacts from the mass and energy flows estimated by the procedure represent a significant share of the impacts assessed in the case study. In a verification, LCI-data from existing processes yielded results within the range of the estimated best-case and worst-case scenarios. Note that verification data could not be obtained for all process steps. From the verification results, it was inferred that mass and energy flows of existing processes for the production of fine and speciality chemicals correspond more frequently to the estimated best-case than to the worst-case scenario. In the sensitivity analysis, solvent demand was found to be the most crucial parameter in the environmental performance of the chemical production processes assessed. Conclusion  Mass and energy flows in LCIs of production processes for fine and speciality chemicals should not be neglected, even if only little information on a process is available. The estimation procedure described here helps to overcome lacking information in a transparent, consistent way. Recommendations and Outlook  Additional verifications and a more detailed estimation of the default parameters are desirable to learn more about the accuracy of the estimation procedure. The procedure should also be applied to case studies to gain insight into the usefulness of the estimation results in different decision-making contexts.