Validation of the species sensitivity distribution in retrospective risk assessment of herbicides at the river basin scale—the Scheldt river basin case study

Species sensitivity distribution (SSD) is commonly used in prospective risk assessment to derive predicted no-effect concentrations, toxicity exposure ratios, and environmental quality standards for individual chemicals such as pesticides. The application of SSD in the retrospective risk assessment of chemical mixtures at the river basin scale (i.e., the estimation of “multiple substance potentially affected fractions” [msPAFs]) has been suggested, but detailed critical assessment of such an application is missing. The present study investigated the impact of different data validation approaches in a retrospective model case study focused on seven herbicides monitored at the Scheldt river basin (Belgium) between 1998 and 2009. The study demonstrated the successful application of the SSD approach. Relatively high impacts of herbicides on aquatic primary producers were predicted. Often, up to 40 % of the primary producer communities were affected, as predicted by chronic msPAF, and in some cases, the predicted impacts were even more pronounced. The risks posed by the studied herbicides decreased during the 1998–2009 period, along with decreasing concentrations of highly toxic pesticides such as simazine or isoproturon. Various data validation approaches (the removal of duplicate values and outliers, the testing of different exposure durations and purities of studied herbicides, etc.) substantially affected SSD at the level of individual studied compounds. However, the time-consuming validation procedures had only a minor impact on the outcomes of the retrospective risk assessment of herbicide mixtures at the river basin scale. Selection of the appropriate taxonomic group for SSD calculation and selection of the species-specific endpoint (i.e., the most sensitive or average value per species) were the most critical steps affecting the final risk values predicted. The present validation study provides a methodological basis for the practical use of SSD in the retrospective risk assessment of chemical mixtures.     

MODELKEY. Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity (5 pp)

BACKGROUND: Triggered by the requirement of Water Framework Directive for a good ecological status for European river systems till 2015 and by still existing lacks in tools for cause identification of insufficient ecological status MODELKEY (http:// www.modelkey.org), an Integrated Project with 26 partners from 14 European countries, was started in 2005. MODELKEY is the acronym for 'Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity'. The project is funded by the European Commission within the Sixth Framework Programme. OBJECTIVES: MODELKEY comprises a multidisciplinary approach aiming at developing interlinked tools for an enhanced understanding of cause-effect-relationships between insufficient ecological status and environmental pollution as causative factor and for the assessment and forecasting of the risks of key pollutants on fresh water and marine ecosystems at a river basin and adjacent marine environment scale. New modelling tools for risk assessment including generic exposure assessment models, mechanistic models of toxic effects in simplified food chains, integrated diagnostic effect models based on community patterns, predictive component effect models applying artificial neural networks and GIS-based analysis of integrated risk indexes will be developed and linked to a user-friendly decision support system for the prioritisation of risks, contamination sources and contaminated sites. APPROACH: Modelling will be closely interlinked with extensive laboratory and field investigations. Early warning strategies on the basis of sub-lethal effects in vitro and in vivo are provided and combined with fractionation and analytical tools for effect-directed analysis of key toxicants. Integrated assessment of exposure and effects on biofilms, invertebrate and fish communities linking chemical analysis in water, sediment and biota with in vitro, in vivo and community level effect analysis is designed to provide data and conceptual understanding for risk arising from key toxicants in aquatic ecosystems and will be used for verification of various modelling approaches. CONCLUSION AND PERSPECTIVE: The developed tools will be verified in case studies representing European key areas including Mediterranean, Western and Central European river basins. An end-user-directed decision support system will be provided for cost-effective tool selection and appropriate risk and site prioritisation.     

A comparison of statistical methods for deriving freshwater quality criteria for the protection of aquatic organisms

Species sensitivity distributions (SSDs) are increasingly used in both ecological risk assessment and derivation of water quality criteria. However, there has been debate about the choice of an appropriate approach for derivation of water quality criteria based on SSDs because the various methods can generate different values. The objective of this study was to compare the differences among various methods. Data sets of acute toxicities of 12 substances to aquatic organisms, representing a range of classes with different modes of action, were studied. Nine typical statistical approaches, including parametric and nonparametric methods, were used to construct SSDs for 12 chemicals. Water quality criteria, expressed as hazardous concentration for 5 % of species (HC₅), were derived by use of several approaches. All approaches produced comparable results, and the data generated by the different approaches were significantly correlated. Variability among estimates of HC₅ of all inclusive species decreased with increasing sample size, and variability was similar among the statistical methods applied. Of the statistical methods selected, the bootstrap method represented the best-fitting model for all chemicals, while log-triangle and Weibull were the best models among the parametric methods evaluated. The bootstrap method was the primary choice to derive water quality criteria when data points are sufficient (more than 20). If the available data are few, all other methods should be constructed, and that which best describes the distribution of the data was selected.     

Analysis of policy options for promotion of clean and energy efficient technologies in the transport sector in Beijing

As a extra-large city in China, Beijing faces a serious problem with air pollution. In 1998, a package of air pollution control measures was announced by local government. However in order to reach environment target, further policy options have to be explored. Based on previous studies on technology choices for urban transport in Beijing, this paper presents a policy assessment to examine these options. A methodology framework using criteria for policy evaluation was used in the assessment. Here diesel-car, Compressed Natural Gas (CNG) vehicle and Mass Railway based Transport (MRT) were selected, and barriers to their diffusion were identified. For each barrier, a group of policy options to remove the barrier was evaluated by five criteria. A ranking of these policy options is given in this paper.     

Spatially differentiated and source-specific population exposure to ambient urban air pollution

Models assessing exposure to air pollution often focus on macro-scale estimates of exposure to all types of sources for a particular pollutant across an urban study area. While results based on these models may aid policy makers in identifying larger areas of elevated exposure risk, they often do not differentiate the proportion of population exposure attributable to different polluting sources (e.g. traffic or industrial). In this paper, we introduce a population exposure modeling system that integrates air dispersion modeling, Geographic Information Systems (GIS), and population exposure techniques to spatially characterize a source-specific exposure to ambient air pollution for an entire urban population at a fine geographical scale. By area, total population exposure in Dallas County in 2000 was more attributable to vehicle polluting sources than industrial polluting sources at all levels of exposure. Population exposure was moderately correlated with vehicle sources (r = 0.440, p < 0.001) and weakly with industrial sources (r = 0.069, p = 0.004). Population density was strongly correlated with total exposure (r = 0.896, p < 0.001) but was not significantly correlated with individual or combined sources. The results of this study indicate that air quality assessments must incorporate more than industrial or vehicle polluting sources-based population exposure values alone, but should consider multiple sources. The population exposure modeling system proposed in this study shows promise for use by municipal authorities, policy makers, and epidemiologists in evaluating and controlling the quality of the air in the process of urban planning and mitigation measures.     

The spatial scale of organic chemicals in multimedia fate modeling. Recent developments and significance for chemical assessment

In the last years, the spatial range (SR) or characteristic travel distance (CTD) of organic chemicals has found increasing scientific interest as an indicator of the long-range transport (LRT) potential and, in combination with persistence, as a kind of 'hazard' indicator on the exposure level. This development coincides with European debates about more effective and more preventive approaches to the chemicals assessment, and about an international, legally-binding instrument for the phase out of persistent organic pollutants (POPs). Persistence and LRT potential are important issues in these debates. Here, the development of the concept of assessing the spatial scale from early ideas in the 1970s and 1980s to recent studies in the field of multimedia fate and transport modeling is summarized. Different approaches to the modeling of environmental transport (advective and dispersive) and different methods for quantifying the SR or CTD are compared. Relationships between SR or CTD and different persistence measures are analyzed. Comparison of these relationships shows that conclusions for chemical assessment should be based on an evaluation of different persistence and spatial scale measures. The use of SR or CTD and persistence as hazard indicators in the chemicals assessment is illustrated.     

Modeling exposure to particulate matter

Exposure assessment, a component of risk assessment, links sources of pollution with health effects. Exposure models are scientific tools used to gain insights into the processes affecting exposure assessment. The purpose of this paper is to review the process and methodology of estimating inhalation exposure to particulate matter (PM) using various types of models. Three types of models are discussed in the paper. Indirect type of models are physical models that employ inventories of outdoor and indoor sources and their emission rates to identify major sources contributing to exposure to PM, and use fate and transport and indoor air quality models to estimate PM concentrations at receptor sites. PM concentrations and time spent by a subject at each receptor site are input variables to the conventional exposure model that estimates the desired exposure levels. Direct type models use measured exposure or exposure concentrations in conjunction with information obtained from questionnaires to formulate exposure regression models. Stochastic models use exposure measurements, estimates can also be used, to formulate exposure population distributions and investigate associated uncertainty and variability. Since models developed using databases from western countries are not necessarily applicable in developing countries, the difference in requirements among western and developing countries is highlighted in the paper. Employment of exposure modeling methods in developing countries requires development of local information. Such information includes local outdoor and indoor source inventories, local or regional meteorological conditions, adjustment of indoor models to reflect local building construction conditions, and use of questionnaires to obtain local time budget and activity patterns of the subject population.     

Rapid assessment of environmental health risks posed by mining operations in low- and middle-income countries: selected case studies

Previous studies have evaluated associated health risks and human exposure pathways at mining sites. Others have provided estimates of the scale of the issue based in part on surveys. However, a global census of mining-related hazardous waste sites has been lacking. The Toxic Sites Identification Program (TSIP) implemented by Blacksmith Institute (New York, NY, USA) since 2009 is an ongoing effort to catalogue a wide range of chemically contaminated sites with a potential human health risk (Ericson et al., Environ Monit Assess doi:10.1007/s 10661-012-2665-2, 2012). The TSIP utilizes a rapid assessment instrument, the Initial Site Screening (ISS), to quickly and affordably identify key site criteria including human exposure pathways, estimated populations at risk, and sampling information. The resulting ISS allows for comparison between sites exhibiting different contaminants and pollution sources. This paper explores the results of a subset of ISSs completed at 131 artisanal and small-scale gold mining areas and 275 industrial mining and ore processing sites in 45 countries. The authors show that the ISS captures key data points, allowing for prioritization of sites for further investigation or remedial activity.     

Even-Aged and Uneven-Aged Forest Management in Boreal Fennoscandia: A Review

Since WWII, forest management in Fennoscandia has primarily been based on even-aged stand management, clear cut harvesting and thinning from below. As an alternative, uneven-aged management, based on selection cutting of individual trees or small groups of trees, has been proposed. In this review we discuss the theoretical aspects of ecology and economics of the two management approaches. We also review peer-reviewed studies from boreal Fennoscandia, which have aimed at comparing the outcomes of uneven-aged and the conventional even-aged forest management. According to a common view the main obstacle of practicing uneven-aged forestry is its low economic performance. However, the reviewed studies did not offer any straightforward support for this view and several studies have found uneven-aged management to be fully competitive with existing even-aged management. Studies on the ecological aspects indicated that selection cuttings maintain mature or late-successional forest characteristics and species assemblages better than even-aged management, at least at the stand scale and in the short term. We conclude that although the number of relevant studies has increased in recent years, the ecological and economic performance of alternative management methods still remains poorly examined, especially for those stands with multiple tree species and also at wider spatial and temporal scales. For future research we advocate a strategy that fully takes into consideration the interdisciplinary nature of forest management and is better connected to social goals and latest theoretical and methodological developments in ecology and economics.     

Evaluation of Methodologies for Exposure Assessment to Atmospheric Pollutants from a Landfill Site

Abstract

Epidemiological studies around landfill sites are limited by several factors, particularly a lack of accurate exposure assessment. Traditionally, exposure estimates are based on distance between place of residence and the landfill site. However, this measure of exposure ignores the effects that environmental factors may have upon exposure. A previous epidemiological study at a landfill site in the United Kingdom provided the basis for a case study to investigate exposure assessment methodologies that could support ongoing and future epidemiological work. Estimation of relative exposure to atmospheric pollutants near the site was refined using the Atmospheric Dispersion Modeling System (ADMS) 3.1. Annual average concentrations were calculated around the landfill site, which was modeled as an area source with a steady release rate over its entire active surface. Local meteorological and terrain data were used in the assessment. A geographical information system (GIS) was then used to link the results of the modeling to population and other data. Sensitivity studies were included to examine the variation of predicted exposure with several modeling assumptions and hence set other uncertainties in context. No simple relationship existed between the relative individual exposure measured by distance from the site and by dispersion modeling. A reassessment of exposure assessment in epidemiological studies around landfill sites was then undertaken with the refined estimates of exposure. This concluded that use of distance from the site as a proxy for exposure could lead to significant exposure misclassification in comparison with exposure assessment using atmospheric dispersion modeling and GIS. The study also indicated that assessment of peak exposure rates (i.e., extreme concentration levels) might be necessary in some epidemiological work. Optimum strategies for increasing the probability of observing effects in the more highly exposed population can be derived by combining the results of dispersion modeling with population data and, where feasible, knowledge of the toxicology of the substances of interest.     

Model selection and evaluation for risk assessment of dioxin-contaminated sites

The general European population has a total intake of dioxins and dioxin-like chemicals near the limit recommended by the European Union, making additional exposure above background levels undesirable. For populations living near dioxin-contaminated sites, additional exposure may occur by intake of locally produced food, inhalation of particles, dermal contact with soils, or other exposure pathways. Risk assessment tools are required to estimate risks associated with contaminated sites and to set priorities for site remediation. Here, we review several multimedia models that can be applied as tools to support risk assessment. We then present a strategy to select, apply, evaluate, and adapt a model to address a specific situation. The case study we consider is a risk assessment of generic background dioxin exposure in Sweden, and we compare the predictions with environmental observations and exposure data from Sweden. Arguments are presented for selecting the CalTOX model for this case study. We demonstrate the application, evaluation, and adaptation of the model and discuss the requirements for extending the analysis to conduct risk assessment for subpopulations living near dioxin-contaminated sites.     

Mixture risk assessment due to ingestion of arsenic,copper, and zinc from milkfish farmed in contaminated coastal areas

Human health risks associated with the consumption of metal-contaminated fish over extended periods have become a concern particularly in Taiwan, where fish is consumed on a large scale. This study applied the interaction-based hazard index (HI) to assess the mixture health risks for fishers and non-fishers who consume the arsenic (As), copper (Cu), and zinc (Zn) contaminated milkfish from As-contaminated coastal areas in Taiwan, taking into account joint toxic actions and potential toxic interactions. We showed that the interactions of As–Zn and Cu–Zn were antagonistic, whereas As–Cu interaction was additive. We found that HI estimates without interactions considered were 1.3–1.6 times higher than interactive HIs. Probability distributions of HI estimates for non-fishers were less than 1, whereas all 97.5%-tile HI estimates for fishers were >1. Analytical results revealed that the level of inorganic As in milkfish was the main contributor to HIs, indicating a health risk posed to consumers of fish farmed in As-contaminated areas. However, we found that Zn supplementation could significantly decrease As-induced risk of hematological effect by activating a Zn-dependent enzyme. In order to improve the accuracy of health risk due to exposure to multiple metals, further toxicological data, regular environmental monitoring, dietary survey, and refinement approaches for interactive risk assessment are warranted.     

When is a soil remediated? Comparison of biopiled and windrowed soils contaminated with bunker-fuel in a full-scale trial

A six month field scale study was carried out to compare windrow turning and biopile techniques for the remediation of soil contaminated with bunker C fuel oil. End-point clean-up targets were defined by human risk assessment and ecotoxicological hazard assessment approaches. Replicate windrows and biopiles were amended with either nutrients and inocula, nutrients alone or no amendment. In addition to fractionated hydrocarbon analysis, culturable microbial characterisation and soil ecotoxicological assays were performed. This particular soil, heavy in texture and historically contaminated with bunker fuel was more effectively remediated by windrowing, but coarser textures may be more amendable to biopiling. This trial reveals the benefit of developing risk and hazard based approaches in defining end-point bioremediation of heavy hydrocarbons when engineered biopile or windrow are proposed as treatment option.     

On the translation of uncertainty from toxicokinetic to toxicodynamic models--the TCDD example

When estimating human health risks from exposure to TCDD using toxicokinetic and toxicodynamic models, it is important to understand how model choice and assumptions necessary for modeling add to the uncertainty of risk estimates. Several toxicokinetic models have been proposed for the risk assessment of dioxins, in particular the elimination kinetics in humans has been a matter of constant debate. For a long time, a simple linear elimination kinetics has been common choice. Thus, it was used for the statistical analysis of the largest occupationally exposed cohort, the German Boehringer cohort. We challenge this assumption by considering, amongst others, a nonlinear modified Michaelis-Menten-type elimination kinetics, the so-called Carrier kinetics. Using the area under the lipid TCDD concentration time curve as dose metrics, we model the time to cancer-related death using the Cox proportional hazards model as toxicodynamic model. This risk assessment set-up was simulated in order to quantify uncertainty of both the dose (TCDD body burden) and the risk estimates, depending on the use of the kinetic model, variations of carcinogenic effect of TCDD and variations of latency period (lag time). If past exposure is estimated assuming a linear elimination kinetics although a Carrier kinetics actually holds, then high exposures in reality will be underestimated through statistical analysis and low exposures will be overestimated, respectively. This bias will carry over on the estimated individual concentration-time curves and the therefrom derived TCDD dose metric values. Using biased dose values when estimating a dose-response relationship will finally lead to biased risk estimates. The extent of bias and the decrease of precision are quantified in selected scenarios through this simulation approach. Our findings are in concordance with recent results in the field of dioxin risk assessment. They also reinforce the general demand for the scheduled uncertainty assessments in risk analyses.     

Pesticide Environmental Accounting: a method for assessing the external costs of individual pesticide applications

The Pesticide Environmental Accounting (PEA) tool provides a monetary estimate of environmental and health impacts per hectare-application for any pesticide. The model combines the Environmental Impact Quotient method and a methodology for absolute estimates of external pesticide costs in UK, USA and Germany. For many countries resources are not available for intensive assessments of external pesticide costs. The model converts external costs of a pesticide in the UK, USA and Germany to Mediterranean countries. Economic and policy applications include estimating impacts of pesticide reduction policies or benefits from technologies replacing pesticides, such as sterile insect technique. The system integrates disparate data and approaches into a single logical method. The assumptions in the system provide transparency and consistency but at the cost of some specificity and precision, a reasonable trade-off for a method that provides both comparative estimates of pesticide impacts and area-based assessments of absolute impacts.     

A framework for risk characterization of environmental pollutants.

Risk characterization is defined by both the U.S. National Academy of Sciences and the U.S. EPA as the estimation of human health risk due to harmful (i.e., toxic or carcinogenic) substances or organisms. Risk characterization studies are accomplished by integrating quantitative exposure estimates and dose-response relationships with the qualitative results of hazard identification. A Risk Characterization Framework has been developed to encourage a systematic approach for analysis and presentation of risk estimates. This methodology subdivides the four common components of the risk assessment process into ten elements. Each of these elements is based on a term in a predictive risk equation. The equation allows independent computations of exposure, dose, lifetime individual risk, and risk to affected populations. All key assumptions in the predictive risk equation can be explicitly shown. This is important to understand the basis and inherent uncertainties of the risk estimation process. The systematic treatment of each of the ten elements in this framework aids in the difficult job of comparing risk estimates by different researchers using different methodologies. The Risk Characterization Framework has been applied to various indoor and outdoor air pollutants of a carcinogenic nature. With further development, it also promises to be applicable to noncarcinogenic effects.     

Socioeconomic consequences of mercury use and pollution

In the past, human activities often resulted in mercury releases to the biosphere with little consideration of undesirable consequences for the health of humans and wildlife. This paper outlines the pathways through which humans and wildlife are exposed to mercury. Fish consumption is the major route of exposure to methylmercury. Humans can also receive toxic doses of mercury through inhalation of elevated concentrations of gaseous elemental mercury. We propose that any effective strategy for reducing mercury exposures requires an examination of the complete life cycle of mercury. This paper examines the life cycle of mercury from a global perspective and then identifies several approaches to measuring the benefits of reducing mercury exposure, policy options for reducing Hg emissions, possible exposure reduction mechanisms, and issues associated with mercury risk assessment and communication for different populations.     

The Sensitivity of Probabilistic Risk Assessment Results to Alternative Model Structures: A Case Study of Municipal Waste Incineration

Abstract

In this analysis, human health risk due to exposure to municipal waste incinerator emissions is assessed as an example of the application of probabilistic techniques (e.g., Monte Carlo or Latin Hypercube simulations). Incinerator risk assessments are characterized by the dominance of indirect exposure, thus this analysis focuses on exposure via the ingestion of locally grown foods. In addition, since exposure to 2, 3, 7, 8-TCDD drives most incinerator risk assessments, this compound is the subject of the illustrative calculations. An important part of probabilistic risk assessment is determining the relative influence of the input parameters on the magnitude of the variance in the output distribution. This constitutes an important step toward prioritizing data needs for additional research. However, under various possible model forms reflecting incompletely understood aspects of contaminant transport, differences may be observed in estimates of risk, variance in risk, and the relative contributions of individual uncertain and variable inputs to the variance. In this analysis, a sequential structural decomposition of the relationships between the input variables is used to partition the variance in the output (i.e., risk) to identify the most influential contributors to overall variance among them. For comparison, the partitioning of variance is repeated, using techniques of multivariate regression. In summary, this study considers the degree to which results of a probabilistic assessment are contingent on critical model assumptions about the representation of deposition velocity. Specifically, this analysis assesses the impact on the results of uncertainty about the best model of the vapor/particle partitioning behavior of semi-volatile airborne pollutants.