Site-specific applications of probabilistic health risk assessment: review of the literature since 2000

Major influencing factors identification and probabilistic health risk assessment of soil potentially toxic elements pollution in coal and metal mines across China: A systematic review

Deposition of potentially toxic elements (PTEs) in soils due to different types of mining activities has been an increasingly important concern worldwide. Quantitative differences of soil PTEs contamination and related health risk among typical mines remain unclear. Herein, data from 110 coal mines and 168 metal mines across China were analyzed based on 265 published literatures to evaluate pollution characteristics, spatial distribution, and probabilistic health risks of soil PTEs. The results showed that PTE levels in soil from both mine types significantly exceeded background values. The geoaccumulation index (Igeo) revealed metal-mine soil pollution levels exceeded those of coal mines, with average Igeo values for Cd, Hg, As, Pb, Cu, and Zn being 3.02-15.60 times higher. Spearman correlation and redundancy analysis identified natural and anthropogenic factors affecting soil PTE contamination in both mine types. Mining activities posed a significant carcinogenic risk, with metal-mine soils showing a total carcinogenic risk an order of magnitude higher than in coal-mine soils. This study provides policymakers a quantitative foundation for developing differentiated strategies for sustainable remediation and risk-based management of PTEs in typical mining soils.

Source-specific risk judgement and environmental impact of potentially toxic elements in fine road dust from an integrated industrial city, North China

The contamination of potentially toxic elements (PTEs) in road dust of large industrial cities is extremely serious. Determining the priority risk control factors of PTE contamination in road dust is critical to enhance the environmental quality of such cities and mitigate the risk of PTE pollution. The Monte Carlo simulation (MCS) method and geographical models were employed to assess the probabilistic pollution levels and eco-health risks of PTEs originating from different sources in fine road dust (FRD) of large industrial cities, and to identify key factors affecting the spatial variability of priority control sources and target PTEs. It was observed that in FRD of Shijiazhuang, a typical large industrial city in China, more than 97% of the samples had an INI > 1 (INI_mean = 1.8), indicating moderately contaminated with PTEs. The eco-risk was at least considerable (NCRI >160) with more than 98% of the samples, mainly caused by Hg (E_{i (mean)} = 367.3). The coal-related industrial source (NCRI_(mean) = 235.1) contributed 70.9% to the overall eco-risk (NCRI_(mean) = 295.5) of source-oriented risks. The non-carcinogenic risk of children and adults are of less importance, but the carcinogenic risk deserves attention. The coal-related industry is a priority control pollution source for human health protection, with As corresponding to the target PTE. The major factors affecting the spatial changes of target PTEs (Hg and As) and coal-related industrial sources were plant distribution, population density, and gross domestic product. The hot spots of coal-related industrial sources in different regions were strongly interfered by various human activities. Our results illustrate spatial changes and key-influencing factors of priority source and target PTEs in Shijiazhuang FRD, which are helpful for environmental protection and control of environmental risks by PTEs.

Source-oriented probabilistic health risk assessment of soil potentially toxic elements in a typical mining city

Identifying potential sources of soil potentially toxic elements (PTEs) and developing source-oriented health risk assessments in typical mining cities are key for pollution prevention and risk management. To this end, a case study was conducted to explore the pollution characteristics, potential sources, and human health risks of PTEs in Daye City, China. Indices, including the pollution factor (PF), pollution load index (PLI), and geo-accumulation index (I_geo), were applied to assess PTE pollution. Cd had the highest value among the detected PTEs, and 82.93% of the sampling sites had moderate pollution levels, with the highest mean I_geo value for Cd (2.30). Four potential sources were determined. Cr and Ni originated mainly from natural sources. Zn (91.5%) was exclusively and then Cd (33.1%) was moderately derived from industrial activities. The mixed source of various mineral exploitation smelting, and coal-fired traffic emissions leaded to the accumulation of As, Cd, and Pb. Cu was associated with Cu-related mining and smelting activities. The probabilistic health risk assessment indicated that the non-carcinogenic risks for populations were negligible. Overall, this work provides scientific information for environmental managers to manage soil PTE pollution through the effective management of anthropogenic sources with limited resources and costs.

Risk Analysis Approaches to Evaluating Health Impacts from Land-Based Pollution in Low- and Middle-Income Countries

Risk analysis offers a useful framework for evaluating and managing environmental health risks across different settings. In this Perspective, we question whether the principles and practice of risk analysis could be beneficial in the context of land-based pollution in low- and middle-income countries (LMICs) to better support risk-based decision making. Specifically, potential health and economic impacts from land-based pollution in LMICs has become an increasing issue of concern due to widespread environmental contamination from active and legacy operations, particularly informal activities that are becoming increasingly dispersed throughout communities, such as used lead acid battery recycling, artisanal and small-scale gold mining, and small-scale tanneries. However, the overall magnitude and scale of the public health problem arising from these sources remains highly uncertain and poorly characterized and cannot be compared to land-based pollution in high-income countries due to unique factors. This lack of knowledge has negatively affected the political priority and level of funding for risk mitigation actions targeting land-based pollution in these countries. Our primary objective is to raise further awareness of this emerging issue among risk analysts and decisionmakers and to advocate for more robust and focused research. Here, we highlight the types of industries and activities contributing to land-based pollution in LMICs and describe key findings and knowledge and data gaps that have hindered a fuller understanding of this issue. We also discuss how several risk assessment and risk management approaches might be useful in this resource-constrained context. We conclude that a combination of risk analysis approaches may be worthwhile, but more work is needed to determine which methods or tools will be most informative, technically feasible, and cost-effective for identifying, prioritizing, and mitigating land-based pollution in LMICs. Affected researchers, funding agencies, and local or national governments will need to work together to develop improved study designs and risk mitigation strategies.

Key Factors for Improving the Carcinogenic Risk Assessment of PAH Inhalation Exposure by Monte Carlo Simulation

Monte Carlo simulation (MCS) is a computational technique widely used in exposure and risk assessment. However, the result of traditional health risk assessment based on the MCS method has always been questioned due to the uncertainty introduced in parameter estimation and the difficulty in result validation. Herein, data from a large-scale investigation of individual polycyclic aromatic hydrocarbon (PAH) exposure was used to explore the key factors for improving the MCS method. Research participants were selected using a statistical sampling method in a typical PAH polluted city. Atmospheric PAH concentrations from 25 sampling sites in the area were detected by GC-MS and exposure parameters of participants were collected by field measurement. The incremental lifetime cancer risk (ILCR) of participants was calculated based on the measured data and considered to be the actual carcinogenic risk of the population. Predicted risks were evaluated by traditional assessment method based on MCS and three improved models including concentration-adjusted, age-stratified, and correlated-parameter-adjusted Monte Carlo methods. The goodness of fit of the models was evaluated quantitatively by comparing with the actual risk. The results showed that the average risk derived by traditional and age-stratified Monte Carlo simulation was 2.6 times higher, and the standard deviation was 3.7 times higher than the actual values. In contrast, the predicted risks of concentration- and correlated-parameter-adjusted models were in good agreement with the actual ILCR. The results of the comparison suggested that accurate simulation of exposure concentration and adjustment of correlated parameters could greatly improve the MCS. The research also reveals that the social factors related to exposure and potential relationship between variables are important issues affecting risk assessment, which require full consideration in assessment and further study in future research.

Application of a health risk assessment model for cattle exposed to pesticides in contaminated drinking waters: A study case from the Pampas region, Argentina

Using the USEPA methodology we estimated the probabilistic chronic risks for calves and adult cows due to pesticide exposure through oral intake of contaminated surface and ground waters in Tres Arroyos County (Argentina). Because published data on pesticide toxicity endpoints for cows are scarce, we used threshold levels based on interspecies extrapolation methods. The studied waters showed acceptable quality for cattle production since none of the pesticides were present at high-enough concentrations to potentially affect cow health. Moreover, ground waters had better quality than surface waters, with dieldrin and deltamethrin being the pesticides associated with the highest risk values in the former and the latter water compartments, respectively. Our study presents a novel use of the USEPA risk methodology proving it is useful for water quality evaluation in terms of pesticide toxicity for cattle production. This approach represents an alternative tool for water quality management in the absence of specific cattle pesticide regulatory limits.

Regional probabilistic risk assessment of heavy metals in different environmental media and land uses: An urbanization-affected drinking water supply area

In this study, we proposed a Regional Probabilistic Risk Assessment (RPRA) to estimate the health risks of exposing residents to heavy metals in different environmental media and land uses. The mean and ranges of heavy metal concentrations were measured in water, sediments, soil profiles and surface soils under four land uses along the Shunde Waterway, a drinking water supply area in China. Hazard quotients (HQs) were estimated for various exposure routes and heavy metal species. Riverbank vegetable plots and private vegetable plots had 95th percentiles of total HQs greater than 3 and 1, respectively, indicating high risks of cultivation on the flooded riverbank. Vegetable uptake and leaching to groundwater were the two transfer routes of soil metals causing high health risks. Exposure risks during outdoor recreation, farming and swimming along the Shunde Waterway are theoretically safe. Arsenic and cadmium were identified as the priority pollutants that contribute the most risk among the heavy metals. Sensitivity analysis showed that the exposure route, variations in exposure parameters, mobility of heavy metals in soil, and metal concentrations all influenced the risk estimates.

The risk of overestimating the risk-metal leaching to groundwater near contaminated glass waste deposits and exposure via drinking water

This study investigates metal contamination patterns and exposure to Sb, As, Ba, Cd and Pb via intake of drinking water in a region in southeastern Sweden where the production of artistic glass has resulted in a large number of contaminated sites. Despite high total concentrations of metals in soil and groundwater at the glassworks sites properties, all drinking water samples from households with private wells, located at a 30-640m distance from a glassworks site, were below drinking water criteria from the WHO for Sb, As, Ba and Cd. A few drinking water samples showed concentrations of Pb above the WHO guideline, but As was the only element found in concentrations that could result in human exposure near toxicological reference values. An efficient retention of metals in the natural soil close to the source areas, which results in a moderate impact on local drinking water, is implied. Firstly, by the lack of significant difference in metal concentrations when comparing households located upstream and downstream of the main waste deposits, and secondly, by the lack of correlation between the metal concentration in drinking water and distance to the nearest glassworks site. However, elevated Pb and Cd concentrations in drinking water around glassworks sites when compared to regional groundwater indicate that diffuse contamination of the soils found outside the glassworks properties, and not only the glass waste landfills, may have a significant impact on groundwater quality. We further demonstrate that different mobilization patterns apply to different metals. Regarding the need to use reliable data to assess drinking water contamination and human exposure, we finally show that the conservative modelling approaches that are frequently used in routine risk assessments may result in exposure estimates many times higher than those based on measured concentrations in the drinking water that is actually being used for consumption.

Application of Probabilistic Risk Assessment in Establishing Perchlorate and Goitrogen Risk Mitigation Strategies

This paper applies probabilistic risk assessment in quantifying risks from cumulative and aggregate risk pathways for selected goitrogens in water and food. Results show that the percentages of individuals with a Hazard Index (HI) value above 1 ranges between 30% and 50% both with and without serum half-life correction when a traditional regulatory assessment approach based on establishment of a No Observed Effects Level (NOEL) is used. When an exposure-response curve is instead used and a threshold of 50% inhibition is assumed, 1.1% or less of the population exceeds an HI value of 1 with no serum half-life correction, rising to as high as 11% when serum half-life correction is applied. If 0% to 5% threshold for iodide uptake inhibition is assumed for production of adverse effects, the percentage of the population with an HI above 1 is 46.2% or less with no serum half-life correction, and 47.2% or less when serum half-life correction is applied. The probabilistic analysis shows that while there are exposed groups for whom perchlorate exposures are the primary cause of individuals having HI values above 1, these constitute significantly less than 1% of the population. Instead, the potential risk from exposure to goitrogens is dominated by nitrates without serum half-life correction and thiocyanates with serum half-life correction, suggesting public health protection is better accomplished by a focus on these and other goitrogens expect in highly limited cases where waterborne perchlorate is at unusually high concentrations.

Assessing the risk of an excess fluoride intake among Swedish children in households with private wells--expanding static single-source methods to a probabilistic multi-exposure-pathway approach

It is often assumed that water consumption is the major route of exposure for fluoride and analysis of water fluoride content is the most common approach for ensuring that the daily intake is not too high. In the present study, the risk of excess intake was characterized for children in households with private wells in Kalmar County, Sweden, where the natural geology shows local enrichments in fluorine. By comparing water concentrations with the WHO drinking water guideline (1.5 mg/L), it was found that 24% of the ca. 4800 sampled wells had a concentration above this limit, hence providing a figure for the number of children in the households concerned assessed to be at risk using this straightforward approach. The risk of an excess intake could, alternatively, also be characterized based on a tolerable daily intake (in this case the US EPA RfD of 0.06 mg/kg-day). The exposure to be evaluated was calculated using a probabilistic approach, where the variability in all exposure factors was considered, again for the same study population. The proportion of children assessed to be at risk after exposure from drinking water now increased to 48%, and when the probabilistic model was adjusted to also include other possible exposure pathways; beverages and food, ingestion of toothpaste, oral soil intake and dust inhalation, the number increased to 77%. Firstly, these results show how the risk characterization is affected by the basis of comparison. In this example, both of the reference values used are widely acknowledged. Secondly, it illustrates how much of the total exposure may be overlooked when only focusing on one exposure pathway, and thirdly, it shows the importance of considering the variability in all relevant pathways.

Application of the Bayesian approach for derivation of PDFs for concentration ratio values

Concentration ratios (CRs) are used to derive activity concentrations in wild plants and animals. Usually, compilations of CR values encompass a wide range of element-organism combinations, extracted from different studies with statistical information reported at varying degrees of detail. To produce a more robust estimation of distribution parameters, data from different studies are normally pooled using classical statistical methods. However, there is inherent subjectivity involved in pooling CR data in the sense that there is a tacit assumption that the CRs under any arbitrarily defined biota category belong to the same population. Here, Bayesian inference has been introduced as an alternative way of making estimates of distribution parameters of CRs. This approach, in contrast to classical methods, is more flexible and also allows us to define the various assumptions required, when combining data, in a more explicit manner. Taking selected data from the recently compiled wildlife transfer database (http://www.wildlifetransferdatabase.org/) as a working example, attempts are made to refine the pooling approaches previously used and to consider situations when empirical data are limited.

Climate change - An uncertainty factor in risk analysis of contaminated land

Metals frequently occur at contaminated sites, where their potential toxicity and persistence require risk assessments that consider possible long-term changes. Changes in climate are likely to affect the speciation, mobility, and risks associated with metals. This paper provides an example of how the climate effect can be inserted in a commonly used exposure model, and how the exposure then changes compared to present conditions. The comparison was made for cadmium (Cd) exposure to 4-year-old children at a highly contaminated iron and steel works site in southeastern Sweden. Both deterministic and probabilistic approaches (through probability bounds analysis, PBA) were used in the exposure assessment. Potential climate-sensitive variables were determined by a literature review. Although only six of the total 39 model variables were assumed to be sensitive to a change in climate (groundwater infiltration, hydraulic conductivity, soil moisture, soil:water distribution, and two bioconcentration factors), the total exposure was clearly affected. For example, by altering the climate-sensitive variables in the order of 15% to 20%, the deterministic estimate of exposure increased by 27%. Similarly, the PBA estimate of the reasonable maximum exposure (RME, defined as the upper bound of the 95th percentile) increased by almost 20%. This means that sites where the exposure in present conditions is determined to be slightly below guideline values may in the future exceed these guidelines, and risk management decisions could thus be affected. The PBA, however, showed that there is also a possibility of lower exposure levels, which means that the changes assumed for the climate-sensitive variables increase the total uncertainty in the probabilistic calculations. This highlights the importance of considering climate as a factor in the characterization of input data to exposure assessments at contaminated sites. The variable with the strongest influence on the result was the soil:water distribution coefficient (Kd).

Just who is at risk? The ethics of environmental regulation

The willingness to view risk as part of daily life has vanished. A risk-averse mindset among environmental regulators engenders confusion between the ethics of intention and the ethics of consequence, leading to the elevation of the precautionary principle with unintended and often unfortunate outcomes. Environmental risk assessment is conservative, but the actual level of conservatism cannot be determined. High-end exposure assumptions and current toxicity criteria from the USEPA, based on linear extrapolation for carcinogens and default uncertainty factors for systemic toxicants, obscure the degree of conservatism in risk assessments. Ideally, one could choose a percentile of the target population to include within environmental standards, but this choice is complicated by the food, pharmaceutical and advertising industries, whose activities, inadvertent or not, often promote maladaptive and unhealthy lifestyle choices. There has lately been much discussion about background exposures and disease processes and their potential to increase the risk from environmental chemicals. Should these background exposures or disease processes, especially those associated with maladaptive individual choices, be included as part of a regulatory risk evaluation? A significant ethical question is whether environmental regulation should protect those pursuing a self-destructive lifestyle that may add to or synergize with otherwise innocuous environmental exposures. Choosing a target percentile of protection would provide an increased level of transparency and the flexibility to choose a higher or lower percentile if such a choice is warranted. Transparency and flexibility will lead to more responsive environmental regulation that balances protection of public health and the stewardship of societal resources.

Screening and prioritisation of chemical risks from metal mining operations, identifying exposure media of concern

Metals have been central to the development of human civilisation from the Bronze Age to modern times, although in the past, metal mining and smelting have been the cause of serious environmental pollution with the potential to harm human health. Despite problems from artisanal mining in some developing countries, modern mining to Western standards now uses the best available mining technology combined with environmental monitoring, mitigation and remediation measures to limit emissions to the environment. This paper develops risk screening and prioritisation methods previously used for contaminated land on military and civilian sites and engineering systems for the analysis and prioritisation of chemical risks from modern metal mining operations. It uses hierarchical holographic modelling and multi-criteria decision making to analyse and prioritise the risks from potentially hazardous inorganic chemical substances released by mining operations. A case study of an active platinum group metals mine in South Africa is used to demonstrate the potential of the method. This risk-based methodology for identifying, filtering and ranking mining-related environmental and human health risks can be used to identify exposure media of greatest concern to inform risk management. It also provides a practical decision-making tool for mine acquisition and helps to communicate risk to all members of mining operation teams.

Uncertainties in ecological, chemical and physiological parameters of a bioaccumulation model: implications for internal concentrations and tissue based risk quotients

Bioaccumulation models predict internal contaminant concentrations (c(i)) using ecological, chemical and physiological parameters. Here we analyse the effect of uncertainties on these parameters on bioaccumulation model predictions. Simultaneously considering the uncertainties on all these parameters in a bioaccumulation model resulted in uncertainty ranges of c(i) that increased with the octanol water partition coefficient K(ow) and reached maxima of up to 1.25 log units for mesozooplankton and up to 1.45 log units fish at logK(ow)=8. A global sensitivity analysis (SA) was performed to rank the contribution of different parameters to the observed uncertainty. The SA demonstrated that this interspecies difference resulted predominantly from uncertain production rates of fish. The K(ow), the water concentration and organic carbon-octanol proportionality constant were important drivers of uncertainty on c(i) for both species. A tissue based risk quotient (RQ(tissue)) combining uncertainty on c(i) with realistic tissue based effect thresholds indicated that fish were up to 10 times more probable to have RQ(tissue)>1 than mesozooplankton, depending on the considered threshold value. Conventional exposure based risk quotients were up to 5 times less probable to exceed one than were corresponding RQ(tissue), and this for both species.

Exposure to contaminated sediments during recreational activities at a public bathing place

More and more time is spent on recreational activities, but few risk assessments focus specifically on these situations and exposure factor data are often scarce. To assess exposure to contaminants at a public bathing place in an urban environment, we have compiled literature data, conducted observation studies, and analyzed water and sediment samples. The levels of anthropogenic contaminants are high in urban environments and traffic frequently plays an important role. In this study, to characterize variability and uncertainty, the deterministic exposure calculations for metal pollutants were supplemented by a probability bounds analysis for the polycyclic aromatic hydrocarbons (PAH). The results from these calculations show that oral intake is the major exposure route for metals, while skin absorption, with present assumptions, is more important for the PAH. The presently measured levels of contaminants, at this public bathing place, cannot be anticipated to cause any significant adverse influence on public health. This assessment methodology is easy to adapt and can be used routinely in other situations with more heavily contaminated surface sediments and lake water.

Incorporating ecological data and associated uncertainty in bioaccumulation modeling: methodology development and case study

Bioaccumulation models predict internal concentrations of hydrophobic chemicals by incorporating key gain/loss processes reflecting the ecology of the exposed species and the characteristics of the chemical. Here, we propose a new methodology that uses ecological data and the principle of mass balance in food webs to estimate bioaccumulation in food webs. To this end, we combine linear inverse models (LIMs) that estimate food web flows based on mass balance with a mechanistic bioaccumulation model (OMEGA). In a case study we show that uncertainty ranges on bioaccumulation predictions were on average estimated a factor of 4 lower by LIM-OMEGA than by an OMEGA application that does not consider mass balance within food webs, most notably for chemicals with log Kow > 5, reflecting an increasing importance of uptake through food ingestion for those chemicals. Ranges of internal concentrations predicted by LIM-OMEGA were smaller in enclosures with fish, as strong predation pressure from the latter on mesozooplankton constrains food web flows and thus bioaccumulation.

Applicability of a neuroprobabilistic integral risk index for the environmental management of polluted areas: a case study

Recently, we developed a GIS-Integrated Integral Risk Index (IRI) to assess human health risks in areas with presence of environmental pollutants. Contaminants were previously ranked by applying a self-organizing map (SOM) to their characteristics of persistence, bioaccumulation, and toxicity in order to obtain the Hazard Index (HI). In the present study, the original IRI was substantially improved by allowing the entrance of probabilistic data. A neuroprobabilistic HI was developed by combining SOM and Monte Carlo analysis. In general terms, the deterministic and probabilistic HIs followed a similar pattern: polychlorinated biphenyls (PCBs) and light polycyclic aromatic hydrocarbons (PAHs) were the pollutants showing the highest and lowest values of HI, respectively. However, the bioaccumulation value of heavy metals notably increased after considering a probability density function to explain the bioaccumulation factor. To check its applicability, a case study was investigated. The probabilistic integral risk was calculated in the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain), where an environmental program has been carried out since 2002. The risk change between 2002 and 2005 was evaluated on the basis of probabilistic data of the levels of various pollutants in soils. The results indicated that the risk of the chemicals under study did not follow a homogeneous tendency. However, the current levels of pollution do not mean a relevant source of health risks for the local population. Moreover, the neuroprobabilistic HI seems to be an adequate tool to be taken into account in risk assessment processes.