Uncertainties in human health risk assessment of environmental contaminants: A review and perspective

Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an ‘adequate’ protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making.     

Sources of uncertainty in model predictions: lessons learned from the IAEA Forest and Fruit Working Group model intercomparisons

The International Atomic Energy Agency (IAEA), through the BIOMASS program, has provided a unique international forum for assessing the relative contribution of different sources of uncertainty associated with environmental modeling. The methodology and guidance for dealing with parameter uncertainty have been fairly well developed and quantitative tools such as Monte-Carlo modeling are often recommended. The issue of model uncertainty is still rarely addressed in practical applications and the use of several alternative models to derive a range of model outputs (similar to what was done in IAEA model intercomparisons) is one of a few available techniques. This paper addresses the often overlooked issue of what we call 'modeler uncertainty,' i.e., differences in problem formulation, model implementation and parameter selection originating from subjective interpretation of the problem at hand. This study uses results from the Fruit and Forest Working Groups created under the BIOMASS program (BIOsphere Modeling and ASSessment). The greatest uncertainty was found to result from modelers' interpretation of scenarios and approximations made by modelers. In scenarios that were unclear for modelers, the initial differences in model predictions were as high as seven orders of magnitude. Only after several meetings and discussions about specific assumptions did the differences in predictions by various models merge. Our study shows that the parameter uncertainty (as evaluated by a probabilistic Monte-Carlo assessment) may have contributed over one order of magnitude to the overall modeling uncertainty. The final model predictions ranged between one and three orders of magnitude, depending on the specific scenario. This study illustrates the importance of problem formulation and implementation of an analytic-deliberative process in fate and transport modeling and risk characterization.     

Application of cattle manure as fertilizer in pastureland: estimating the incremental risk due to metal accumulation employing a multicompartment model

Specific-site data of metal concentration in cattle manure from NW Spain and a multicompartment fate and exposure model were used to evaluate metal fate and the main routes of exposure after a 100 year period of application of cattle manure as fertiliser in pastureland. Risk assessment was performed as a probabilistic analysis, and using a conservative worst-case exposure scenario. An accumulation model was used to predict the metal concentration in each environmental medium of concern. The incremental risk was estimated for the population inhabiting the surroundings of the area by a general multiexposure model. Monte Carlo simulations were performed to analyse uncertainty of the results. Furthermore, a sensitivity analysis was carried out to identify the contribution to variance by the different metals and exposure routes. Among the five pathways evaluated, the ingestion of meat and milk from cattle grazing in the area represents the main contribution to total exposure. The results indicate that the incremental risk to human health for people living in the surroundings of pasturelands due to continuous application of cattle manure after a 100 year period are not negligible for the metals considered (Cd, Cu, Ni, Pb and Zn), posing a total Reasonable Maximum Exposure (RME) of 0.75, being the ingestion of meat the main exposure pathway.     

Cancer risk assessment of selected hazardous air pollutants in Seattle

The risk estimates calculated from the conventional risk assessment method usually are compound specific and provide limited information for source-specific air quality control. We used a risk apportionment approach, which is a combination of receptor modeling and risk assessment, to estimate source-specific lifetime excess cancer risks of selected hazardous air pollutants. We analyzed the speciated PM(2.5) and VOCs data collected at the Beacon Hill in Seattle, WA between 2000 and 2004 with the Multilinear Engine to first quantify source contributions to the mixture of hazardous air pollutants (HAPs) in terms of mass concentrations. The cancer risk from exposure to each source was then calculated as the sum of all available species' cancer risks in the source feature. We also adopted the bootstrapping technique for the uncertainty analysis. The results showed that the overall cancer risk was 6.09 x 10(-5), with the background (1.61 x 10(-5)), diesel (9.82 x 10(-6)) and wood burning (9.45 x 10(-6)) sources being the primary risk sources. The PM(2.5) mass concentration contributed 20% of the total risk. The 5th percentile of the risk estimates of all sources other than marine and soil were higher than 110(-6). It was also found that the diesel and wood burning sources presented similar cancer risks although the diesel exhaust contributed less to the PM(2.5) mass concentration than the wood burning. This highlights the additional value from such a risk apportionment approach that could be utilized for prioritizing control strategies to reduce the highest population health risks from exposure to HAPs.     

Assessing concentrations and health impacts of air quality management strategies: Framework for Rapid Emissions Scenario and Health impact ESTimation (FRESH-EST)

In air quality management, reducing emissions from pollutant sources often forms the primary response to attaining air quality standards and guidelines. Despite the broad success of air quality management in the US, challenges remain. As examples: allocating emissions reductions among multiple sources is complex and can require many rounds of negotiation; health impacts associated with emissions, the ultimate driver for the standards, are not explicitly assessed; and long dispersion model run-times, which result from the increasing size and complexity of model inputs, limit the number of scenarios that can be evaluated, thus increasing the likelihood of missing an optimal strategy. A new modeling framework, called the “Framework for Rapid Emissions Scenario and Health impact ESTimation” (FRESH-EST), is presented to respond to these challenges. FRESH-EST estimates concentrations and health impacts of alternative emissions scenarios at the urban scale, providing efficient computations from emissions to health impacts at the Census block or other desired spatial scale. In addition, FRESH-EST can optimize emission reductions to meet specified environmental and health constraints, and a convenient user interface and graphical displays are provided to facilitate scenario evaluation. The new framework is demonstrated in an SO₂ non-attainment area in southeast Michigan with two optimization strategies: the first minimizes emission reductions needed to achieve a target concentration; the second minimizes concentrations while holding constant the cumulative emissions across local sources (e.g., an emissions floor). The optimized strategies match outcomes in the proposed SO₂ State Implementation Plan without the proposed stack parameter modifications or shutdowns. In addition, the lower health impacts estimated for these strategies suggest that FRESH-EST could be used to identify potentially more desirable pollution control alternatives in air quality management planning.     

Approaches for describing and communicating overall uncertainty in toxicity characterizations: U.S. Environmental Protection Agency's Integrated Risk Information System (IRIS) as a case study

Single point estimates of human health hazard/toxicity values such as a reference dose (RfD) are generally used in chemical hazard and risk assessment programs for assessing potential risks associated with site- or use-specific exposures. The resulting point estimates are often used by risk managers for regulatory decision-making, including standard setting, determination of emission controls, and mitigation of exposures to chemical substances. Risk managers, as well as stakeholders (interested and affected parties), often have limited information regarding assumptions and uncertainty factors in numerical estimates of both hazards and risks. Further, the use of different approaches for addressing uncertainty, which vary in transparency, can lead to a lack of confidence in the scientific underpinning of regulatory decision-making. The overarching goal of this paper, which was developed from an invited participant workshop, is to offer five approaches for presenting toxicity values in a transparent manner in order to improve the understanding, consideration, and informed use of uncertainty by risk assessors, risk managers, and stakeholders. The five approaches for improving the presentation and communication of uncertainty are described using U.S. Environmental Protection Agency's (EPA's) Integrated Risk Information System (IRIS) as a case study. These approaches will ensure transparency in the documentation, development, and use of toxicity values at EPA, the Agency for Toxic Substances and Disease Registry (ATSDR), and other similar assessment programs in the public and private sector. Further empirical testing will help to inform the approaches that will work best for specific audiences and situations.     

Addressing uncertainties in the ERICA Integrated Approach

Like any complex environmental problem, ecological risk assessment of the impacts of ionising radiation is confounded by uncertainty. At all stages, from problem formulation through to risk characterisation, the assessment is dependent on models, scenarios, assumptions and extrapolations. These include technical uncertainties related to the data used, conceptual uncertainties associated with models and scenarios, as well as social uncertainties such as economic impacts, the interpretation of legislation, and the acceptability of the assessment results to stakeholders. The ERICA Integrated Approach has been developed to allow an assessment of the risks of ionising radiation, and includes a number of methods that are intended to make the uncertainties and assumptions inherent in the assessment more transparent to users and stakeholders. Throughout its development, ERICA has recommended that assessors deal openly with the deeper dimensions of uncertainty and acknowledge that uncertainty is intrinsic to complex systems. Since the tool is based on a tiered approach, the approaches to dealing with uncertainty vary between the tiers, ranging from a simple, but highly conservative screening to a full probabilistic risk assessment including sensitivity analysis. This paper gives on overview of types of uncertainty that are manifest in ecological risk assessment and the ERICA Integrated Approach to dealing with some of these uncertainties.     

Retrospective exposure assessment in a chemical research and development facility

The objective of this exposure assessment was to reconstruct cumulative historical exposures for workers who have been exposed to multiple chemicals and chemical groups to better understand a cluster of brain cancers within a research and development lab. Chemicals of interest, including acrylates, bis-chloromethyl ether (BCME), chloromethyl methyl ether (CMME), isothiazolones and nitrosoamines, were selected on the basis of the plausibility of penetrating the blood-brain barrier and the uniqueness of the chemical's biological activity.In a complicated exposure setting such as a chemical R&D facility, multiple exposure estimation methods were needed. First, similarly exposure groups (SEGs) were created for these materials based on department group, time period of the department's existence and function associated with job titles. A probabilistic framework for assessing exposures was developed using Bayesian analysis of historical monitoring data, mathematical exposure modeling and professional judgments of current and former industrial hygienists at the facility were used to reconstruct the exposure history for acrylates, BCME and CMME for each SEG over the time period of interest. Since sufficient measurement data for isothiazolones and nitrosoamines were not available, the exposure histories for each SEG for these chemicals were estimated. This was done using objective formaldehyde levels and subjective employee interviews. The interviews assessed workplace determinants of exposure as distinct surrogates for estimating inhalation and dermal exposures. The exposure assessments by these methods were compared against each other to estimate the potential for exposure misclassification. A job exposure matrix (JEM) was constructed that contained the exposures obtained from above multiple approaches for each of these chemical groups for each SEG for each year of interest. The combination of methods used in this work is a unique and potentially helpful framework that can be used in analogous workplace settings involving multiple exposures with incomplete objective measurement information.     

城市土地置换过程中土壤多环芳烃污染的健康风险评价

利用健康风险评价方法判定污染土壤是否需要修复或再次开发已成为一个新的研究领域。以某区域土地置换开发为案例，结合区域未来土地利用类型，采用健康风险评价模型对土壤多环芳烃（PAHs）污染可能给未来入住人群带来的健康风险进行初步评价。结果显示，在正常情况与极端情况两种暴露场合下，考虑直接接触不慎摄入、呼吸土壤尘和皮肤直接接触土壤3种途径，计算出的土壤PAHs污染的致癌风险相对较高，部分点位已经超过了人体健康可接受的致癌风险程度。且以敏感人群儿童为例，利用摄入量和风险评价反推得出，当土壤中PAHs含量低于634 μg/kg时，在极端情况下，儿童致癌风险可降低到可接受的致癌风险水平。随着环境管理工作的深入发展，在城市土地置换过程中应逐步加强环境健康风险评价方面的研究。     

Transfer of dioxin risk between nine major municipal waste incinerators in Taiwan

The objective of this study was to assess site-specific carcinogenic risks of incinerator-emitted dioxins and risk transfers among the areas covered by nine municipal incinerators in Taiwan. We used actual emission data and the industrial source complex short-term model (ISCST3) to determine the dioxin impact areas within the 8 x 8-km simulation regions surrounding the incinerators. We then used multimedia model to estimate cancer risks in individual impact areas for two exposure scenarios, which were sufficient (SFP) and insufficient food production (IFP) for residents' consumption in each impact area. We also used information of food supply and consumption between impact areas to calculate risk transfers among these nine incinerators. We found that dioxins' carcinogenic risks ranged from 1.4 x 10(-8) (Incinerator F) to 7.1 x 10(-5) (Incinerator A) for the nine incinerators under the exposure scenario of SFP, and ranged from 8.7 x 10(-8) (Incinerator D) to 1.1 X 10(-6) (Incinerator E) under the exposure scenario of IFP. The food ingestion was the main exposure pathway, which accounted for 64-99% of total dioxin risks among nine impact areas. For the nine major food items consumed by residents in the impact areas, eggs (14-35%) and chicken (11-26%) were two main routes of dioxin exposure in the SFP scenario, while chicken (8-78%) and vegetables (0.2-81%) were two main routes of dioxin exposure in the IFP scenario. Significant risks of dioxins were transferred among incinerators, which accounted for up to 88% among the incinerators. Incinerator E was the major risk-exporting source to six Incinerators C, D, F, G, H, and I. For these six incinerators, Incinerator E accounted for their 51-88% imported risks. We concluded that risk transfers among incinerators through routes of food consumption should be considered in assessing health risks associated with incinerator-emitted dioxins in Taiwan. We should place high priority on implementing control measures to lower dioxin emissions in important food-exporting areas like Incinerator E. We should also emphasize analyzing dioxin contents in eggs, chicken, and vegetables in order to improve dioxin-related health risk assessments in the future.     

Distributions of personal VOC exposures: a population-based analysis

Information regarding the distribution of volatile organic compound (VOC) concentrations and exposures is scarce, and there have been few, if any, studies using population-based samples from which representative estimates can be derived. This study characterizes distributions of personal exposures to ten different VOCs in the U.S. measured in the 1999-2000 National Health and Nutrition Examination Survey (NHANES). Personal VOC exposures were collected for 669 individuals over 2-3 days, and measurements were weighted to derive national-level statistics. Four common exposure sources were identified using factor analyses: gasoline vapor and vehicle exhaust, methyl tert-butyl ether (MBTE) as a gasoline additive, tap water disinfection products, and household cleaning products. Benzene, toluene, ethyl benzene, xylenes chloroform, and tetrachloroethene were fit to log-normal distributions with reasonably good agreement to observations. 1,4-Dichlorobenzene and trichloroethene were fit to Pareto distributions, and MTBE to Weibull distribution, but agreement was poor. However, distributions that attempt to match all of the VOC exposure data can lead to incorrect conclusions regarding the level and frequency of the higher exposures. Maximum Gumbel distributions gave generally good fits to extrema, however, they could not fully represent the highest exposures of the NHANES measurements. The analysis suggests that complete models for the distribution of VOC exposures require an approach that combines standard and extreme value distributions, and that carefully identifies outliers. This is the first study to provide national-level and representative statistics regarding the VOC exposures, and its results have important implications for risk assessment and probabilistic analyses.     

Effect of user interpretation on uncertainty estimates: examples from the air-to-milk transfer of radiocesium

An important source of uncertainty in predictions of numerical simulation codes of environmental transport processes arises from the assumptions made by the user when interpreting the model and the scenario to be assessed. This type of uncertainty was examined systematically in this study and was compared with uncertainty due to varying parameter values in a code. Three terrestrial food chain codes that are driven by deposition of radionuclides from the atmosphere were used by up to ten participants to predict total deposition of ¹³⁷Cs and concentrations on pasture and in milk for two release scenarios. Collective uncertainty among the predictions of the ten users for concentrations in milk calculated for one scenario by one code was a factor of 2000, while the largest individual uncertainty was 20 times lower. Choice of parameter values contributed most to user-induced uncertainty, followed by scenario interpretation. Due to the significant disparity in predictions, it is recommended that assessments should not be carried out alone by a single code user.     

Framing climate uncertainty: socio-economic and climate scenarios in vulnerability and adaptation assessments

Scenarios have become a powerful tool in integrated assessment and policy analysis for climate change. Socio-economic and climate scenarios are often combined to assess climate change impacts and vulnerabilities across different sectors and to inform risk management strategies. Such combinations of scenarios can also play an important role in enabling the interaction between experts and other stakeholders, framing issues and providing a means for making explicit and dealing with uncertainties. Drawing on experience with the application of scenarios to climate change assessments in recent Dutch research, the paper argues that scenario approaches need to be matched to the frames of stakeholders who are situated in specific decision contexts. Differentiated approaches (top-down, bottom-up and interactive) are needed to address the different frames and decision-making contexts of stakeholders. A framework is proposed to map scenarios and decision contexts onto two dimensions: the spatial scale of the context and the starting point of approach used in scenario development (top-down, bottom-up or incident-driven). Future climate and socio-economic scenario development will be shaped by the need to become better aligned with multiple interacting uncertainties salient to stakeholders.     

城市土地置换过程中土壤多环芳烃污染的健康风险评价

利用健康风险评价方法判定污染土壤是否需要修复或再次开发已成为一个新的研究领域。以某区域土地置换开发为案例，结合区域未来土地利用类型，采用健康风险评价模型对土壤多环芳烃（PAHs）污染可能给未来入住人群带来的健康风险进行初步评价。结果显示，在正常情况与极端情况两种暴露场合下，考虑直接接触不慎摄入、呼吸土壤尘和皮肤直接接触土壤3种途径，计算出的土壤PAHs污染的致癌风险相对较高，部分点位已经超过了人体健康可接受的致癌风险程度。且以敏感人群儿童为例，利用摄入量和风险评价反推得出，当土壤中PAHs含量低于634 μg/kg时，在极端情况下，儿童致癌风险可降低到可接受的致癌风险水平。随着环境管理工作的深入发展，在城市土地置换过程中应逐步加强环境健康风险评价方面的研究。     

Assessment of regional climate change impacts on Hungarian landscapes

The assessment of regional climate change impacts combined with the sensitivity of landscape functions by predictive modelling of hazardous landscape processes is a new fundamental field of research. In particular, this study investigates the effects of changing weather extremes on meso-regional-scale landscape vulnerability. Climatic-exposure parameter analysis was performed on a predicted climate change scenario. The exposure to climate change was analysed on the basis of the original data of the meso-scale IPCC A1B climate scenario from the REMO and ALADIN regional models for the periods of 2021–2050 and 2071–2100, and the regional types of climate change impacts were calculated by using cluster analysis. Selected climate exposure parameters of the REMO and ALADIN models were analysed, in particular, for extreme events (days with precipitation greater than 30 mm, heat waves, dry periods, wet periods) and for daily temperature and precipitation. The landscape functions impacted by climate change are proxies for the main recent and future problematic processes in Hungary. Soil erosion caused by water, drought, soil erosion caused by wind, mass movement and flash floods were analysed for the time periods of 1961–1990, 2021–2050 and 2071–2100. Based on the sensitivity thresholds for the impact assessments, the landscape functional sensitivity indicators were interpreted, and an integrative summary of the five indicators was made, differentiating the regions facing only a few or multiple sensitivities. In Central Hungary, the increasing exposure and sensitivity to droughts will be a serious problem when following the REMO scenario. In several regions, most indicators will change the sensitivity threshold from a tolerable risk to an increased or very high risk.     

Development of quantitative estimates of uncertainty in environmental risk assessments when the scientific data base is inadequate

The reasons for developing quantitative estimates of uncertainty in environmental risk assessments are discussed along with a method for developing them which involves scientific judgement. In the situation considered here the regulatory needs are ahead of the science, which makes the development of the estimates on uncertainty more difficult, but not impossible. Quantitative estimates for all uncertainties involved in the estimation of risk resulting from exposure to volatile organic compounds (VOCs) in drinking water are developed and tabulated. By far the largest contribution to the uncertainty in the risk estimates for VOCs in drinking water are due to uncertainty in the extrapolation of the dose-response curve to low levels. The uncertainty due to extrapolation is on the order of 10⁴ and 10⁶. Other components of the analysis may contribute uncertainties of a few orders of magnitude. In general the largest uncertainties are in the toxicological data base and the manipulation of it needed to estimate risk. The data base and manipulations needed to estimate exposure due to VOCs in drinking water were at the more an order to magnitudes in uncertainty.     

Hydropower development in the lower Mekong basin: alternative approaches to deal with uncertainty

Governments in the Lower Mekong Basin (LMB) face decisions that involve trade-offs between the economic benefits from hydropower generation and potentially irreversible negative impacts on the ecosystems that provide livelihoods and food security to the rural poor. As a means of comparing these trade-offs, a sensitivity analysis of the benefit-cost analysis of certain Basin Development Plan (BDP) scenarios was undertaken. By changing some key assumptions in the BDP about discount rates, the value of lost capture fisheries, future aquaculture production in the LMB, and the value of lost ecosystem services from wetlands to reflect the full range of uncertainty, at the extremes, there could be a reversal of the Net Present Value (NPV) estimates of the scenarios from a positive $33 billion to negative $274 billion. This report recommends when dealing with large-scale, complex projects: a more comprehensive, integrated human and natural systems framework and adaptive management approach to LMB planning and development that deals with the entire watershed; a more comprehensive analysis and treatment of risk and uncertainty; a more thorough assessment of the value of direct and indirect ecosystem services; a broader set of scenarios that embody alternative models of development, broader stakeholder participation; and better treatment of the effects of infrastructure construction on local cultures and the poor.     

Pollutant exposures and health symptoms in aircrew and office workers: Is there a link?

Sensory effects in eyes and airways are common symptoms reported by aircraft crew and office workers. Neurological symptoms, such as headache, have also been reported. To assess the commonality and differences in exposures and health symptoms, a literature search of aircraft cabin and office air concentrations of non-reactive volatile organic compounds (VOCs) and ozone-initiated terpene reaction products were compiled and assessed. Data for tricresyl phosphates, in particular tri-ortho-cresyl phosphate (ToCP), were also compiled, as well as information on other risk factors such as low relative humidity.A conservative health risk assessment for eye, airway and neurological effects was undertaken based on a “worst-case scenario” which assumed a simultaneous constant exposure for 8 h to identified maximum concentrations in aircraft and offices. This used guidelines and reference values for sensory irritation for eyes and upper airways and airflow limitation; a tolerable daily intake value was used for ToCP. The assessment involved the use of hazard quotients or indexes, defined as the summed ratio(s) (%) of compound concentration(s) divided by their guideline value(s).The concentration data suggest that, under the assumption of a conservative “worst-case scenario”, aircraft air and office concentrations of the compounds in question are not likely to be associated with sensory symptoms in eyes and airways. This is supported by the fact that maximum concentrations are, in general, associated with infrequent incidents and brief exposures. Sensory symptoms, in particular in eyes, appear to be exacerbated by environmental and occupational conditions that differ in aircraft and offices, e.g., ozone incidents, low relative humidity, low cabin pressure, and visual display unit work. The data do not support airflow limitation effects. For ToCP, in view of the conservative approach adopted here and the rareness of reported incidents, the health risk of exposure to this compound in aircraft is considered negligible.     

A spatial risk assessment methodology to support the remediation of contaminated land

When soil and groundwater contaminations occur over large areas, remediation measures should be spatially prioritized on the basis of the risk posed to human health and in compliance with technological and budget constraints. Within this scope, the application of human health risk assessment algorithms in a spatially resolved environment raises a number of methodological and technical complexities. In this paper, a methodology is proposed and applied in a case study to support the entire formulation process of remediation plans, encompassing hazard assessment, exposure assessment, risk characterisation, uncertainty assessment and allocation of risk reduction measures. In the hazard assessment, it supports the selection of Contaminants of Concern (CoC) with regard to both their average concentrations and peak concentrations, i.e. hot spots. In the exposure assessment, it provides a zoning of the site based on the geostatistical mapping of contaminant. In the risk characterisation, it generates vector maps of Risk Factors on the basis of the risk posed by multiple substances and allows the interrogation of most relevant CoC and exposure pathways for each zone of the site. It also supports the Monte Carlo based probabilistic estimation of the Risk Factors and generates maps of the associated uncertainty. In the risk reduction phase, it supports the formulation of remediation plans based on the stepwise spatial allocation of remediation interventions and the on-time simulation of risk reduction performances. The application of this methodology is fully supported by an easy-to-use and customized Geographical Information System and does not require high expertise for interpretation. The proposed methodology is the core module of a Decision Support System (DSS) that was implemented in the DESYRE software aimed at supporting the risk-based remediation of megasites.