Assessing the risk costs in delineating soil nickel contamination using sequential Gaussian simulation and transfer functions

Geostatistical simulated realization maps can represent the spatial heterogeneity of the studied spatial variable more realistically than the kriged optimal map because they overcome the smoothing effect of interpolation. The difference among realizations indicates spatial uncertainty. These realizations may serve as input data to transfer functions to further evaluate the resulting uncertainty in impacted dependent variables. In this study, sequential Gaussian simulation was used to simulate the spatial distribution of soil nickel (Ni) in the top soils of a 31 km² area within the urban-rural transition zone of Wuhan, China. Simulated realizations were then imported into transfer functions to calculate the health risk costs caused by Ni polluted areas ignored in remediation due to underestimation of the Ni contents and the remediation risk costs caused by unnecessary remediation of unpolluted areas due to overestimation of the Ni contents. The uncertainty about the input Ni content values thus propagated through these transfer functions, leading to uncertain responses in health risk costs and remediation risk costs. The spatial uncertainty of the two forms of risk costs were assessed based on the response realizations. Because the risk of exposure of soil Ni to humans and animals is generally greater in contaminated arable lands than in industrial and residential areas, the effect of land use types was also taken into account in risk cost estimation. Results showed that high health costs mainly appear in the southwest part of the study area, while high remediation costs mainly occur in the east, middle and northwest of the study area, and that most of the south part of the study area was delineated as contaminated according to the minimum expected cost standard. This study shows that sequential Gaussian simulation and transfer functions are valuable tools for assessing risk costs of soil contamination delineation and associated spatial uncertainty.     

A Human Health Risk Assessment Software for Facilitating Management of Urban Contaminated Sites: A Case Study: The Massa Site,Tuscany, Italy

The goal of this article is to present the Human Health Risk Assessment (HRA) software developed as one of the NORISC ^{1 1}NORISC is the acronym of the project “Network Oriented Risk assessment by In-situ Screening of Contaminated sites” realized under under the 5th European Union Community Framework Programme for Research, Technological Development and Demonstration Activities. View all notes decision support software system components that could be used as a tool for facilitating management of urban contaminated sites. The NORISC-HRA software provides sufficient technical and procedural support to conduct a simple site-specific risk assessment. The employed HRA methodology is generally based on U.S. Environmental Protection Agency (USEPA) procedures. The software determines the level and spatial distribution of human health risks at a given site and sets up site-specific preliminary Health-Based Remedial Goals (HBRGs)/Risk-Based Concentrations (RBCs) for soil and groundwater. The NORISC-HRA software is recommended for use when national soil and groundwater limit values are exceeded. Exposure pathways considered in this software are associated with three land use patterns—residential, industrial/commercial, and recreational. The aricle also presents the software testing results obtained at one of the NORISC test sites—the Massa site (Avenza-Carrara, Tuscany, Italy). Findings of the HRA indicated that the contaminated soil at the Massa test site might pose potential cancer and non-cancer risks to industrial workers in its present condition. Arsenic was the dominant substance responsible for most of the baseline risk and at the RBC of 1.77 mg/kg it was the primary driver of remedial decisions at the Massa site.     

Environmental risks posed by heavy metal contamination from mine waste: Case study from northwest Iran

Mining activities produce waste tailings that can be a significant source of pollution in the surrounding ecosystem. This study was designed to estimate the magnitude of Fe, As, Pb, Cd, Mn, Ni, Zn, and Cr in soil impacted by activities in the Moeil iron ore mine area of northwestern Iran and initially assess the potential risk to nearby residents and ecological habitats. For this, concentrations of elements in 24 samples from 8 locations were analyzed by inductivity coupled plasma optical emission spectrometry. Concentrations of heavy metals reported for samples collected from the area ranged from 50,247–466,200 mg/kg for Fe, 40–10,827 mg/kg for As, 9–84 mg/kg for Pb, 0.2–58.4 mg/kg for Cd, 32–424 mg/kg for Mn, 4–32 mg/kg for Ni, 37–60 mg/kg for Zn, and 32–337 mg/kg for Cr. Reported levels of Fe and As in particular are indicative of severe contamination and imply a high risk to ecological receptors. Reported levels of arsenic also imply elevated cancer and non-cancer health risks to residents who work in or pass through the area. Reported levels of Cd and Cr in soil samples also indicate an elevated cancer risk posed by these metals. The result of this study indicates it is important to estimate potential contamination of soils and drinking water wills in the vicinity of Moeil village to arsenic and heavy metals.     

Selecting a more realistic uncertainty factor: Reducing compounding effects of multiple uncertainties

Available toxicology datasets provide a unique opportunity to validate some of the currently used Uncertainty Factors in the development of acceptable exposure levels for noncancer effects. Toxicity studies from two separate sources, the FAO/WHO database on pesticides (1978–1987) and the Monsanto database (through 1988) were chosen to evaluate three of the five currently used Uncertainty Factors. Interspecies differences in NOELs between the three mammalian species evaluated are equal to or less than a factor of 10 for both the FAO/WHO data and the Monsanto data in greater than 90% of the cases evaluated. Median values for the comparison of interspecies NOELs were 3.0 or less for all comparisons except the comparison between the mouse and rat for the Monsanto dataset where the median value was 7.5. Analyses of the Monsanto toxicity database show that the reprotoxicity NOELs were always equivalent to or higher than the chronic or subchronic NOELs for the same material. Therefore, even without conduct of a specific study to address reproductive effects, reasonable protection from adverse reproductive effects can be afforded by use of either subchronic or chronic study NOELs without application of UFD. The median ratio of subchronic NOELs and chronic NOELs was 4, and for a majority of the studies the difference between the NOELs was within one order of magnitude. Our analysis aids in validating the assumption that the upperbound for individual uncertainties maybe accounted for by use of 10‐fold uncertainty factors. However, the current U.S. Environmental Protection Agency (USEPA) reference doses/concentrations may be overly conservative because upperbounds of each of the uncertainty factors are used and each of the uncertainty factors are considered to be independent variables. Because uncertainties are probably not independent variables, the influence of compounding upperbounds when multiple uncertainty factors are used is generally only considered when four or more areas of uncertainty are outstanding. When multiple uncertainties exist, we recommend upperbound estimates only be used for the first two Uncertainty Factors, and median values be used to account for the remaining uncertainties.     

Assessment of Carcinogenic Risk and Non-Carcinogenic Health Hazard from Exposure to Toxicants in Water from the Southwestern Coastal River System in Ghana

This study evaluated cancer risk and non-cancer human health hazard from exposure to the toxicants such as As, Cu, Pb, Zn, Mn, and CN in water from a southwestern river system in Ghana that drains through gold mining areas, using 108 water samples collected with random sampling techniques and analyzed in accordance with standard methods of chemical analysis outlined by the U.S. Environmental Protection Agency (USEPA). The concentrations of Cu and Zn were within World Health Organization and USEPA guideline values; Mn, free cyanide, As, and Pb values in most cases either exceeded USEPA and WHO values or both. The concentrations of the toxicants were used as input parameters in the cancer and non-cancer study that was conducted in line with USEPA risk assessment guidelines. The results of As cancer health risk revealed higher risk cases in two locations (Potroase and Dominase); non-cancer health risk for As was higher in 10 of the 14 locations, with other metals being of health concern at few locations in the study area. In conclusion, the findings of this study hold several policy implications as residents of mining communities still depend on these water bodies as their source of drinking water.     

Treatments of Uncertainty and Variability in Ecological Risk Assessment of Single-Species Populations

The selection of the most appropriate model for an ecological risk assessment depends on the application, the data and resources available, the knowledge base of the assessor, the relevant endpoints, and the extent to which the model deals with uncertainty. Since ecological systems are highly variable and our knowledge of model input parameters is uncertain, it is important that models include treatments of uncertainty and variability, and that results are reported in this light. In this paper we discuss treatments of variation and uncertainty in a variety of population models. In ecological risk assessments, the risk relates to the probability of an adverse event in the context of environmental variation. Uncertainty relates to ignorance about parameter values, e.g., measurement error and systematic error. An assessment of the full distribution of risks, under variability and parameter uncertainty, will give the most comprehensive and flexible endpoint. In this paper we present the rationale behind probabilistic risk assessment, identify the sources of uncertainty relevant for risk assessment and provide an overview of a range of population models. While all of the models reviewed have some utility in ecology, some have more comprehensive treatments of uncertainty than others. We identify the models that allow probabilistic assessments and sensitivity analyses, and we offer recommendations for further developments that aim towards more comprehensive and reliable ecological risk assessments for populations.     

Simplified MPN method for enumeration of soil naphthalene degraders using gaseous substrate

We describe a simplified microplate most-probable-number (MPN) procedure to quantify the bacterial naphthalene degrader population in soil samples. In this method, the sole substrate naphthalene is dosed passively via gaseous phase to liquid medium and the detection of growth is based on the automated measurement of turbidity using an absorbance reader. The performance of the new method was evaluated by comparison with a recently introduced method in which the substrate is dissolved in inert silicone oil and added individually to each well, and the results are scored visually using a respiration indicator dye. Oil-contaminated industrial soil showed slightly but significantly higher MPN estimate with our method than with the reference method. This suggests that gaseous naphthalene was dissolved in an adequate concentration to support the growth of naphthalene degraders without being too toxic. The dosing of substrate via gaseous phase notably reduced the work load and risk of contamination. The result scoring by absorbance measurement was objective and more reliable than measurement with indicator dye, and it also enabled further analysis of cultures. Several bacterial genera were identified by cloning and sequencing of 16S rRNA genes from the MPN wells incubated in the presence of gaseous naphthalene. In addition, the applicability of the simplified MPN method was demonstrated by a significant positive correlation between the level of oil contamination and the number of naphthalene degraders detected in soil.     

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.     

Establishing Data-Derived Adjustment Factors from Published Pharmaceutical Clinical Trial Data

In non-cancer risk assessment the goal traditionally has been to protect the majority of people by setting limits that account for interindividual variability in the human population. The Environmental Protection Agency (EPA) has assigned a default uncertainty factor (?UF) of 10 to account for interindividual variability in response to toxic agents in the general population. Previous studies have suggested that it is appropriate to equally divide this factor into sub-factors of 3.2 each for variability in human pharmacokinetics (PK) and pharmacodynamics (PD). As an extension of this model, one can envision using scientific data from the literature to modify the default sub-factors with compound-specific adjustment factors (AFs) and to create new and more scientifically based defaults. In this paper, data from published clinical trials on six pharmaceutical compounds were used to further illustrate how to calculate and interpret data-derived AFs. The clinical trial data were analyzed for content and the reported mean and standard deviation values for two key PK parameters, area under the curve of blood concentration by time (AUC) and peak plasma concentration (C_max), were evaluated. The mean PK values for each study were subsequently analyzed for variability within the population (unimodal distributions) and for the presence of potentially susceptible sub-populations (bimodal distributions). A method based on the proportion of the population covered was applied and data-derived AFs were calculated for these six compounds. Our results showed that, of the 15 possible data-derived AFs calculated using unimodal and bimodal distributions, only three exceeded a value of 3.2. This study further illustrates the value of calculating data-derived values when sufficient PK data are available.     

Adequacy Conditions for Reporting Uncertainty in Chemical Risk Assessments

Uncertainty may influence decision-making. A prerequisite for a decision to be well founded is thus that scientific experts inform decision-makers about all decision relevant uncertainty. A set of conditions is provided for adequate characterization of scientific uncertainty for the purposes of regulatory decision-making. These conditions require specification of (1) the character and degree of uncertainty about the assessment variables, (2) the possibility of reducing the uncertainty, and (3) the degree of agreement among experts. Furthermore, it is required that (4) the information covered by the previous conditions is presented in a clear and comprehensible way. The point of departure is that characterizing scientific uncertainty conceptually means specifying all potentially important possibilities that are consistent with the state of scientific knowledge. The conditions are intended to be applied to human health risk assessment of chemicals. However, the basic approach, to consider potentially important possibilities, should be useful also to environmental, and site-specific risk assessment.     

A Probabilistic Assessment of Household Exposures to MTBE from Drinking Water

The oxygenate methyl tertiary butyl ether (MTBE) has been added to reformulated gasoline in the U.S. to meet national ambient air quality standards. Although MTBE has provided significant health benefits in terms of reduced criteria and toxic air pollutants, detections of MTBE in some groundwater and drinking water sources have raised concerns about potential environmental contamination and human exposures. In this paper, we examine the frequency and concentration of MTBE detections in drinking water sources in California from 1995 to 1999, and provide a preliminary analysis of the distribution of household exposures to MTBE from water-related activities. Using published data on the toxicity and possible cancer hazard posed by MTBE, we estimate the likely cancer and non-cancer risks for the general population in California from past and potential future MTBE exposures. More highly exposed subgroups were also addressed. Our findings indicate that less than 2% of all sampled drinking water sources in California had detectable levels of MTBE in 1999, with average MTBE drinking water concentrations ranging from 0.09 to 4.9?ppb for this year. Both the detection rate for MTBE and average MTBE concentrations have remained relatively stable since 1995, despite increased sampling of drinking water sources in California. The probabilistic exposure analysis suggests that drinking water exposures to MTBE are unlikely to pose a significant health risk for the general population or more highly exposed individuals in California.     

Exposure to Crystalline Silica Inhalation Among Construction Workers: A Probabilistic Risk Analysis

Crystalline silica and its presence in dust generated during various construction activities may pose a health hazard to construction workers. In this article, the occupational exposure to crystalline silica and the related long-term health (cancer and non-cancer) risks among construction workers from five different trades (activities) were evaluated using a probabilistic approach. The predicted 95th percentile of the excess lifetime cancer risk and hazard quotients for exposure to crystalline silica ranged from 4.5 × 10^?5 to 1.2 × 10^?4, and 15 to 37, respectively. The efficiency of the state-of-the-art technologies to reduce silica inhalation at construction sites are evaluated in the context of reduction in long-term health risks to the construction workers. The use of engineering controls and personal protective equipments to reduce the exposure to crystalline silica reduced the hazard quotient and excess lifetime cancer risk approximately by 65% and 78%, respectively. The sensitivity analyses showed that the exposure concentration of crystalline silica was the most significant parameter in both cancer and non-cancer risk estimates for the construction workers. The breathing rate, the exposure factor, and the daily shift hours also significantly contribute to the cancer and non-cancer risk estimates for the construction workers.     

Assessment of potential health risk of heavy metals in soils from a rapidly developing region of China

Soil heavy metal contamination is a major environmental concern, and health risk associated with heavy metals is not fully explored. A combination of spatial analysis and Monte Carlo simulation was successfully used to identify the possible sources and health risk of cadmium (Cd), arsenic (As), mercury (Hg), lead (Pb), chromium (Cr), and copper (Cu) in soils collected from a rapidly developing region of China. It was found that mean concentrations of Cd (0.17 mg/kg ), As (8.74 mg/kg ), Hg (0.15 mg/kg ), Pb (27.28 mg/kg ), and Cu (33.32 mg/kg ) were greater than the soil background values. Accumulation and spatial variability of heavy metals were significantly affected by anthropogenic activities and soil properties. The risk assessment indicated that non-carcinogenic risk was not significant. However, 95% of the total cumulative carcinogenic risk of children was greater than 1E-05, implying high potential carcinogenic risk with As and Pb representing the major contributors. Ingestion of heavy metals in the soils was the main exposure pathway compared with the inhalation and the dermal exposure. Concentration of heavy metals in the soils, particulate emission factor, and dermal exposure ratio were the major parameters affecting health risk. This study highlights the importance of assessment of soil direct exposure health risk in studying heavy metal exposures.     

Non-Carcinogenic Risk Assessment of Heavy Metals and Fluoride in Some Water Wells in the Al-Baha Region,Saudi Arabia

On a global scale, pathogenic contamination of drinking water poses the most significant health risk to humans. However, significant risks to human health may also result from exposure to nonpathogenic, toxic contaminants that are often ubiquitous in waters. The purpose of this study is to determine the levels of heavy metal and fluoride contaminants in water wells used in the Al-Baha region, Saudi Arabia, to evaluate if the levels of metals will have non-carcinogenic effects. Samples were collected from private wells in the area and were analyzed for chemical contamination using approved methods of collection and analysis. Chromium, manganese, zinc, iron, and fluoride were detected in all samples, and were selected for toxicological evaluation. Exposure through ingestion and dermal contact were the scenarios proposed in this study. Chronic daily intakes (CDIs) were estimated for both routes and then compared with health guideline values. The non-cancer risk estimations show that manganese, chromium, and zinc individually have oral Hazard Quotient (HQ) values less than a value of one. Iron and fluoride were found to have oral HQ values greater than 1 in some samples. Also, on considering the additive effect of the contaminants we found that some samples have Hazard Index (HI) values greater than 1, which indicates that there is a concern for chronic non-cancer adverse health effects in case of oral and dermal routes of exposure to water from these wells.     

山东省部分水岸带土壤重金属含量及污染评价

为了解山东省水岸带土壤重金属的含量特征和污染状况,于2010年9月—10月采集了39个水岸带土壤样品,分析了土壤中Cr、Co、Ni、Cu、Zn、Cd、Pb和Hg的含量以及土壤的pH值、粒度和有机质,采用单因子指数法、综合指数法和潜在生态危害指数法对水岸带土壤重金属污染进行了评价,并利用相关分析和聚类分析对其来源进行了初步的解析。结果表明：水岸带土壤的pH值为5.67—8.66,主要呈碱性;有机质的平均含量为9.39 g/kg,土壤粒度主要以砂粒和粉粒为主,其平均体积百分比分别为50.33%和38.48%,平均粒径为89.69 μm;Cr、Co、Ni、Cu、Zn、Cd、Pb和Hg的平均含量为53.03 mg/kg、10.33 mg/kg、24.96 mg/kg、18.38 mg/kg、56.13 mg/kg、0.142 mg/kg、22.48 mg/kg和0.020 mg/kg。各水岸带土壤重金属的含量均符合《土壤环境质量标准》（GB15618-1995）二级标准。以山东省土壤元素背景值为评价标准,水岸带土壤重金属总体表现为轻度污染和轻微生态风险,其中Cd和Hg是主要的污染因子,其对潜在生态危害指数的平均贡献率分别为46.8% 和33.6%。洙赵新河、廖河、门楼水库和东平湖水岸带土壤重金属污染及潜在生态危害明显高于其他水源地。源解析的结果表明：水岸带土壤重金属的含量受自然源和人为源的双重影响,人为源主要包括地表径流、工业废气、垃圾和交通运输等。     

Health Risks of Metals in Soil,Water, and Major Food Crops in Hamedan Province,Iran

Food, drinking water, soil, and air are the main routes of exposure to trace metals, thus the assessment of the risks posed to humans by these elements is important. Wheat, potatoes, and maize are very important parts of the Iranian diet. The objectives of this study were to estimate the non-carcinogenic and carcinogenic health risks of Hg, Pb, Cd, Cr, Se, As, and Ni to adults and children via soil, water, and major food crops consumed in Hamedan Province, northwest Iran, using the total non-cancer hazard quotient (THQ) and cancer risk assessment estimates. Total non-cancer hazard of Ni and Hg, were greater than 1, and total cancer risk of As and Pb was greater than 1 × 10^?6. Food consumption was identified as the major route of human exposure to metals, and consuming foodstuff threatens the health of the studied population. In Hamedan Province, consumption of wheat is the main source of intake of metals from foodstuff for adults, and in children, the soil ingestion route is also important.     

A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression,Classification and Regression Tree,and Random Forest Models

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0–20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R² value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R² values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale.     

Soil Cleanup Goal for Dioxin Using Probabilistic Risk Assessment Techniques

State regulators in Florida recently approved a first-of-its-kind probabilistic risk assessment (PRA) for determining an alternative residential Soil Cleanup Target Level (SCTL) for dioxin (32 ng/kg TEQ). The default residential SCTL (7 ng/kg TEQ) is based on a single, deterministic calculation with numerous conservative assumptions, resulting in an overly conservative value far beyond the regulatory mandate (i.e., 10^?6 increase in cancer risk). Conversely, this PRA used a Monte Carlo simulation to estimate risk for all members of a large population using a combination of scientific data and professional judgment, with final details developed during negotiations with regulators. The simulation parameters were defined probabilistically and reflect the ranges of values for the following exposure variables: body weight, exposure duration, exposure frequency, fraction from contaminated source, soil ingestion rate, and relative bioavailability. Other variable and uncertain parameters were treated deterministically per direction from the regulators. The state also required that a pre-supposed high-risk subpopulation be analyzed separate from the full receptor population. Despite the conservativeness of the alternative SCTL, this PRA represents a significant step toward more realistic estimates of human health risks caused by environmental contaminant exposure.     

Human Health Risk Assessment of a Civilian-Accessible Active Firing Range

The Korean Federation of Teachers Association, the Korea Ministry of Education, Science and Technology, and the Korea Ministry of National Defense (KMND) concluded a memorandum of understanding (MOU) on opening military sites to elementary, middle, and high school students to strengthen national security consciousness. According to the MOU, the KMND decided to open an active firing range; however, due to the ongoing firing activity, site contamination by toxic energetic materials (EMs) was suspected. To identify whether opening the firing range might pose a human health threat to the students and their teachers visiting the site, we conducted a risk assessment to evaluate potential risk. The risk assessment results revealed that both cancer risk and non-cancer risk were negligible. The potential cancer risk was in the range of 1.9 × 10^–11 and 1.4 × 10^–10, and the potential non-cancer hazard index was in the range of 2.3 × 10^–6 and 4.9 × 10^–6.