Use of Probabilistic Methods to Understand the Conservatism in California’s Approach to Assessing Health Risks Posed by Air Contaminants

Many state and federal agencies have prepared risk assessment guidelines, which describe methods for quantifying health risks associated with exposure to vapors and particulates emitted from point and area sources (e.g., California Air Pollution Control Officers Association [CAPCOA] under the Air Toxics “Hot Spots” Act [Assembly Bill 2588] and the U.S. Environmental Protection Agency [EPA] under the Clean Air Act). In general, these guidelines recommend or require the use of upper bound “point” estimates for numerous exposure parameters. This methodology yields a single risk estimate, which is intended not to underestimate the true risk and may significantly overstate it. This paper describes a risk assessment of a facility’s airborne emissions using a probabilistic approach, which presents a range and distribution of risk estimates rather than a single point estimate. The health risks to residents living near a food processing facility, as estimated using techniques recommended by California AB2588, are compared to the results of a probabilistic analysis. Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) were identified as the emitted chemicals of concern. The point estimate method recommended by CAPCOA resulted in estimates that were greater than the 99.99th percentile risk predicted by the probabilistic analysis. As shown in other assessments of persistent airborne chemicals, secondary or indirect exposure pathways (i.e., ingestion of beef, ingestion of cow’s milk, and ingestion of mother’s milk) rather than inhalation, were the greatest contributors to risk. In this analysis, the probability distributions for the cancer potency factor and ingestion of cow’s milk had the largest impact on the results of the 33 exposure factors considered.     

Prediction of overall persistence and long-range transport potential with multimedia fate models: robustness and sensitivity of results

The hazard indicators persistence (P) and long-range transport potential (LRTP) are used in chemicals assessment to characterize chemicals with regard to the temporal and spatial extent of their environmental exposure. They are often calculated based on the results of multimedia fate models. The environmental and substance-specific input parameters of such models are subject to a range of methodological uncertainties and also influenced by natural variability. We employed probabilistic uncertainty analysis to quantify variance in P and LRTP predictions for chemicals with different partitioning and transport behavior. Variance found in the results is so large that it prevents a clear distinction between chemicals. Additionally, only small improvements are observed when evaluating the results relative to a benchmark chemical. This can be explained by the dominance of substance-specific parameters and the only small direct influence of environmental parameters on P and LRTP as model outcomes. The findings underline the importance of learning how environmental conditions cause variability in substance behavior for improved substance ranking and classification.     

The use of Monte-Carlo simulation techniques for risk assessment: study of a municipal waste incinerator

The incremental lifetime risks due to polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) for the residents living in the surroundings of a municipal solid waste incinerator (MSWI) have been assessed. Two different pathways of exposure to PCDD/Fs, ingestion through the diet and exposure from MSWI emissions, were compared. Monte-Carlo simulations were carried out to obtain variability and uncertainty propagation The joint analysis of uncertainty and variability included a sensitivity analysis that identified the contribution to variance by different inputs. In general terms, PCDD/F ingestion through the diet contributed with more than 99% of the total risk, whereas direct exposition to PCDD/F emissions from the MSWI was less than 1% The results show that the median (50% percentile) of non-carcinogenic risk due to PCDD/Fs in the population living in the surroundings of the MSWI was 0.72 and the ratio of the 95th percentile and fifth percentile was about 2. With respect to the total carcinogenic risk, the median increment in individual lifetime was 7.90 x 10(-5) while the ratio between the 95th percentile and the fifth percentile was about 1.5. In this analysis, a sequential structural decomposition of the relationships between the input variables has been used to partition the variance in the output (risk) in order to identify the most influential contributors to overall variance among them.     

An updated state of the science EQC model for evaluating chemical fate in the environment: application to D5 (decamethylcyclopentasiloxane)

The EQuilibrium Criterion (EQC) model developed and published in 1996 has been widely used for screening level evaluations of the multimedia, fugacity-based environmental fate of organic chemicals for educational, industrial, and regulatory purposes. Advances in the science of chemical partitioning and reactivity and the need for more rigorous regulatory evaluations have resulted in a need to update the model. The New EQC model is described which includes an improved treatment of input partitioning and reactivity data, temperature dependence and an easier sensitivity and uncertainty analysis but uses the same multi-level approach, equations and environmental parameters as in the original version. A narrative output is also produced. The New EQC model, which uses a Microsoft Excel platform, is described and applied in detail to decamethylcyclopentasiloxane (D5; CAS No. 541-02-6). The implications of these results for the more detailed exposure and risk assessment of D5 are discussed. The need for rigorous evaluation and documentation of the input parameters is outlined.     

Mass balance modelling of contaminants in river basins: application of the flexible matrix approach

It is useful to have available a variety of catchment-scale water quality models that range in complexity, spatial resolution and data requirements. In a previous paper [Warren, C., Mackay, D., Whelan, M., Fox, K., 2005. Mass balance modelling of contaminants in river basins: a flexible matrix approach. Chemosphere 61, 1458-1467] a series of simple to intermediately complex mass balance models was presented which can be used for tiered exposure assessments in river basins. The connectivity of the segments is expressed using a matrix that permits flexibility in application, enabling the model to be re-segmented and applied to different catchments as required. In this paper, the intermediate models, QWASI matrix-rate constant (QMX-R) and QWASI matrix-fugacity (QMX-F) are used to estimate concentrations of linear alkylbenzene sulfonates (LAS) in the rivers Aire and Calder, UK, and of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the Fraser River basin, Canada. The results compare satisfactorily with monitoring data, suggesting that these QWASI-based models for exposure and risk assessment may be applicable under data-limited conditions. The use of QWASI-based models for regulatory purposes in an evaluative river system is also discussed with reference to assessments of para-dichlorobenzene (pDCB), trichloroethylene (TCE), bis(2-ethylhexyl) phthalate (DEHP) and toluene. It is shown that multi-media QWASI model predictions can be usefully depicted graphically on chemical space diagrams and used to highlight regions in which advection, partitioning to sediments and volatilization may be important determinants of chemical fate in river systems.     

Evaluation on subcellular partitioning and biodynamics of pulse copper toxicity in tilapia reveals impacts of a major environmental disturbance

Fluctuation exposure of trace metal copper (Cu) is ubiquitous in aquatic environments. The purpose of this study was to investigate the impacts of chronically pulsed exposure on biodynamics and subcellular partitioning of Cu in freshwater tilapia (Oreochromis mossambicus). Long-term 28-day pulsed Cu exposure experiments were performed to explore subcellular partitioning and toxicokinetics/toxicodynamics of Cu in tilapia. Subcellular partitioning linking with a metal influx scheme was used to estimate detoxification and elimination rates. A biotic ligand model-based damage assessment model was used to take into account environmental effects and biological mechanisms of Cu toxicity. We demonstrated that the probability causing 50% of susceptibility risk in response to pulse Cu exposure in generic Taiwan aquaculture ponds was ~33% of Cu in adverse physiologically associated, metabolically active pool, implicating no significant susceptibility risk for tilapia. We suggest that our integrated ecotoxicological models linking chronic exposure measurements with subcellular partitioning can facilitate a risk assessment framework that provides a predictive tool for preventive susceptibility reduction strategies for freshwater fish exposed to pulse metal stressors.     

Health risk assessment of exposure to organic matter from the use of reclaimed water in toilets

To estimate the carcinogenic and non-carcinogenic risks of six volatile organic compounds (VOCs) found in reclaimed water used for flushing toilets, a probabilistic health risk assessment based on Monte Carlo simulations was used. Before Monte Carlo simulations, the contaminant volatilization model was applied to estimate the concentration of the pollutants in air. Moreover, a questionnaire was used to acquire daily exposure time and the Batch Fit tool of Crystal Ball software was applied to find the best-fitting distribution of a part of the input parameters. The risk analysis indicated that the health risks from six VOCs were lower than the negligible risk level (1?×?10^?8) in all cases, and the health risk for females was slightly higher than that for males. Overall, exposure to organic pollutants in reclaimed water during toilet flushing does not currently pose a significant carcinogenic risk to humans. In this study, we want to provide some information on the health risk from reclaimed water used for toilet flushing in China and hope that it will be useful to promote the application of reclaimed water in water-deficient areas.     

A Maximum Entropy Approach to Estimating Emissions

ABSTRACT

A maximum information entropy method of calculating probabilistic estimates of volatile organic compound (VOC) emissions by the wood furniture and fixture coating industry is presented. The maximum entropy approach is used to produce minimally biased probability distributions for number of firms, coating use, and coating emission factors from existing summary statistics. These distributions are combined to estimate VOC emissions. The maximum entropy emissions estimate provides information to support probabilistic modeling of regional air quality, probabilistic assessment of emission reduction strategies, and risk assessments. Accurate estimation of emission distributions produces more informed regulatory decisionmaking, risk comparisons, and regulatory and scientific priority setting.     

Dispersion modelling of dioxin releases from the waste incinerator at Avonmouth,Bristol, UK

A modified Gaussian atmospheric dispersion model, Industrial Source Complex (ISCST3), is used to estimate toxic equivalent ground level concentrations (GLC) of dioxins emitted from the Avonmouth municipal waste incinerator (MWI) in Bristol, UK. The sensitivity of the predicted GLC to various vapour and particle partitioning scenarios is reported. Predictions incorporating local terrain and actual emission data are used to estimate the mean incremental intake of dioxin due to MWI operation for local residents, through an existing multi-pathway human exposure model. Results are compared with predictions of incremental intake for a generalised MWI. The mean incremental dioxin intake for a hypothetical maximum exposed individual (HMEI) is shown to be up to 46.5% of the background intake compared to only 1.14% for the generalised MWI scenario. This indicates that the use of local terrain and emission data in MWI dispersion modelling is crucial for health risk assessments associated with human dioxin intake, especially in view of the current debate over the tolerable daily intake for dioxins.     

Model comparison for risk assessment: a case study of contaminated groundwater

Many environmental multimedia risk assessment models have been developed and widely used along with increasing sophistication of the risk assessment method. Despite of the considerable improvement, uncertainty remains a primary threat to the credibility of and users' confidence in the model-based risk assessments. In particular, it has been indicated that scenario and model uncertainty may affect significantly the assessment outcome. Furthermore, the uncertainty resulting from choosing different models has been shown more important than that caused by parameter uncertainty. Based on the relationship between exposure pathways and estimated risk results, this study develops a screening procedure to compare the relative suitability between potential multimedia models, which would facilitate the reduction of uncertainty due to model selection. MEPAS, MMSOILS, and CalTOX models, combined with Monte Carlo simulation, are applied to a realistic groundwater-contaminated site to demonstrate the process. It is also shown that the identification of important parameters and exposure pathways, and implicitly, the subsequent design of uncertainty reduction and risk management measures, would be better-formed.     

Analysis of coupled model uncertainties in source-to-dose modeling of human exposures to ambient air pollution: A PM2.5 case study

Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into account linkages and feedbacks. The current state-of-practice for such assessments is to exercise emission, meteorology, air quality, exposure, and dose models separately, and to link them together by using the output of one model as input to the subsequent downstream model. Quantification of variability and uncertainty has been an important topic in the exposure assessment community for a number of years. Variability refers to differences in the value of a quantity (e.g., exposure) over time, space, or among individuals. Uncertainty refers to lack of knowledge regarding the true value of a quantity. An emerging challenge is how to quantify variability and uncertainty in integrated assessments over the source-to-dose continuum by considering contributions from individual as well as linked components. For a case study of fine particulate matter (PM_2.5) in North Carolina during July 2002, we characterize variability and uncertainty associated with each of the individual concentration, exposure and dose models that are linked, and use a conceptual framework to quantify and evaluate the implications of coupled model uncertainties. We find that the resulting overall uncertainties due to combined effects of both variability and uncertainty are smaller (usually by a factor of 3–4) than the crudely multiplied model-specific overall uncertainty ratios. Future research will need to examine the impact of potential dependencies among the model components by conducting a truly coupled modeling analysis.     

Probabilistic risk assessment of abalone Haliotis diversicolor supertexta exposed to waterborne zinc

This paper describes a risk assessment approach that integrates predicted tissue concentrations of zinc (Zn) with a concentration-response relationship and leads to predictions of survival risk for pond abalone Haliotis diversicolor supertexta as well as to the uncertainties associated with these predictions. The models implemented include a probabilistic bioaccumulation model, which linking biokinetic and consumer-resource models, accounts for Zn exposure profile and a modified Hill model for reconstructing a dose-response profile for abalone exposed to waterborne Zn. The growth risk is assessed by hazard quotients characterized by measured water level and chronic no-observed effect concentration. Our risk analyses for H. diversicolor supertexta reared near Toucheng, Kouhu, and Anping, respectively, in north, central, and south Taiwan region indicate a relatively low likelihood that survival is being affected by waterborne Zn. Expected risks of mortality for abalone were estimated as 0.46 (Toucheng), 0.36 (Kouhu), and 0.29 (Anping). The predicted 90th-percentiles of hazard quotient for potential growth risk were estimated as 1.94 (Toucheng), 0.47 (Kouhu), and 0.51 (Anping). These findings indicate that waterborne Zn exposure poses no significant risk to pond abalone in Kouhu and Anping, yet a relative high growth risk in Toucheng is alarming. Because of a scarcity of toxicity and exposure data, the probabilistic risk assessment was based on very conservative assumptions.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.     

Comparative analysis of health risk assessments for municipal waste combustors

Quantitative health risk assessments have been performed for a number of proposed municipal waste combustor (MWC) facilities over the past several years. This article presents the results of a comparative analysis of a total of 21 risk assessments, focusing on seven of the most comprehensive methodologies. The analysis concentrates on stack emissions of noncriteria pollutants and is comparative rather than critical in nature. Overall, the risk assessment methodologies used were similar whereas the assumptions and input values used varied from study to study. Some of this variability results directly from differences in site-specific characteristics, but much of it is due to absence of data, lack of field validation, lack of specific guidelines from regulatory agencies, and reliance on professional judgment. The results indicate that carcinogenic risks are more significant than chronic non-carcinogenic risks. In most instances polychlorodibenzodioxins, polychlorodibenzofurans, and cadmium contribute more significantly to the total carcinogenic risk from MWC stack emissions than other contaminants. In addition, the contribution to total risk of all indirect routes of exposure (ingestion and dermal contact) exceeds that of the direct inhalation route for most studies reviewed.     

Risk-based approach to appraise valve closure in the clam Corbicula fluminea in response to waterborne metals

We developed a risk-based approach to assess how the valve closure behavior of Asiatic clam Corbicula fluminea responds to waterborne copper (Cu) and cadmium (Cd). We reanalyzed the valve closure response data from published literature to reconstruct the response time-dependent dose-response profiles based on an empirical three-parameter Hill equation model. We integrated probabilistic exposure profiles of measured environmental Cu and Cd concentrations in the western coastal areas of Taiwan with the reconstructed dose-response relationships at different integration times of response to quantitatively estimate the valve response risk. The risk assessment results implicate exposure to waterborne Cu and Cd may pose no significant risk to clam valve activity in the short-time response periods (e.g., <30 min), yet a relative high risk for valve closure response to waterborne Cu at response times greater than 120 min is alarming. We successfully linked reconstructed dose-response profiles and EC50-time relationships associated with the fitted daily valve opening/closing rhythm characterized by a three-parameter lognormal function to predict the time-varying bivalve closure rhythm response to waterborne metals. We parameterized the proposed predictive model that should encourage a risk-management framework for discussion of future design of biological monitoring systems.     

Uncertainties and data needs in risk assessment of three commercial polybrominated diphenyl ethers: probabilistic exposure analysis and comparison with European Commission results

Some environmental monitoring programs have reported increasing levels of certain polybrominated diphenyl ether (PBDE) isomers in aquatic biota and in human breast milk. The commercial PBDE products are known as penta-, octa-, and deca-brominated diphenyl ethers (PeBDE, OBDE and DBDE, respectively). Aside from the current European Commission's risk assessment initiative and efforts underway in Sweden, Canada and elsewhere to evaluate environmental levels, little is understood about sources of exposure and risks to humans. In this study, a multi-pathway human health risk assessment was performed to predict theoretical chronic daily intakes (CDIs) of PeBDE, OBDE, and DBDE by five different age groups: 0-2, 2-6, 6-12, 12-18, and 18-70 years. Sources of exposure included air, drinking water, consumption of fish, vegetables, meat and dairy products, and ingestion of breast milk by infants. In addition to a deterministic analysis, the risk assessment included a probabilistic analysis to derive the probability density functions describing the range of plausible exposures associated with eight different pathways, as well as aggregate lifetime exposures for each age group. The results were compared to CDI point estimates calculated by the European Chemicals Bureau as part of the European Commission's Existing Substances Programme. The major sources of uncertainties are discussed, including environmental sources, levels in different environmental compartments, toxicity, and human exposure. This paper also discusses the limitations in the current state-of-the-science and provides recommendations for improving the scientific relevance and accuracy of future environmental risk assessments of PBDEs.     

The current practice of health risk assessment: potential impact on standards for toxic air contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of "plausible" estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

Opportunities for a probabilistic risk assessment of chemicals in the European Union

In risk assessment of new and existing substances, it is current practice to characterise risk using a deterministic quotient of the exposure concentration, or the dose, and a no-effect level. A sense of uncertainty is tackled by introducing worst-case assumptions in the methodology. Since this procedure leads to an assessment with an unknown degree of conservatism, it is advisable to deal quantitatively with uncertainties. This paper discusses the advantages and possibilities of a probabilistic risk assessment framework, illustrated with an example calculation. Furthermore, representatives of EU Member States and the chemical industry were interviewed to find out their views on applying uncertainty analysis to risk assessment of industrial chemicals.     

Health risk analysis of PCDD/F emissions from MSW incineration: comparison of probabilistic and deterministic approaches

Incremental lifetime health risks due to polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) emitted from municipal waste incineration (MSWI) facilities were evaluated for resident population in the area of the plant. Risk assessment was performed through a multipathway combined probabilistic/deterministic approach for analyzing the effects of uncertainty and intrinsic variability of the main PCDD/F emission related parameters on final predicted values. Exposure through direct inhalation of contaminated air, soil ingestion, soil dermal contact and diet were considered, with the propagation of the variability of input parameters throughout the evaluation performed with Monte Carlo simulation techniques. The application to a case study representative of two different technological scenarios (modern facilities equipped with BAT - Best Available Technology - and older incinerators) in a location site typical of Northern Italy situation results in median values of the maximum individual excess risk on the order of 10(-9) and 10(-7) for most recent and older plant configurations, respectively. Corresponding ratios for the 90th and 10th percentile values are around 7 and 9. Individual risk estimates derived for the same scenarios from conventional deterministic approaches, where large conservative assumptions are normally adopted for compensating the lack of knowledge about uncertainty, are essentially comparable with maximum values resulting from the probabilistic approach, thus leading to situations with extreme and very low probabilities of occurrence. PCDD/F health risks from MSWI emissions might thus result largely overestimated if real emission characteristics are not properly considered in the assessment procedure. Sensitivity analysis for identifying the contribution of different input parameters on final predicted risk variance indicates, for the area considered in the simulation, a prevailing influence of PCDD/F stack concentration, with exposures arising from soil deposition phenomena substantially negligible: this latter result further points out the requirements for a very careful identification of base input data values for PCDD/F stack concentrations, at least for those situations where plants are located nearby urban areas.