Publications

We propose a multimedia model-based methodology to evaluate whether a chemical substance qualifies as POP-like based on overall persistence (Pot,) and potential for long-range transport (LRTP). It relies upon screening chemicals against the Pov and LRTP characteristics of selected reference chemicals with well-established environmental fates. Results indicate that chemicals of high and low concern in terms of persistence and long-range transport can be consistently identified by eight contemporary multimedia models using the proposed methodology. Model results for three hypothetical chemicals illustrate that the model-based classification of chemicals according to P,), and LRTP is not always consistent with the single-media half-life approach proposed by the UNEP Stockholm Convention and that the models provide additional insight into the likely long-term hazards associated with chemicals in the environment. We suggest this model-based classification method be adopted as a complement to screening against defined half-life criteria at the initial stages of tiered assessments designed to identify POP-like chemicals and to prioritize further environmental fate studies for new and existing chemicals.

Physicochemical properties (vapor pressure, aqueous solubility, octanol solubility, Henry's law constant, and octanol-air and octanol-water partition coefficients) and their temperature dependencies are required for fate modeling of environmental pollutants. To be internally consistent, measured values for these properties often must be adjusted. The goal of adjusting the property values for consistency is to more accurately estimate the true values. However, consistency and accuracy are not synonymous. If there are systematic errors in one property, then adjustment for consistency may reduce the accuracy of other property data. Here, we provide methods for achieving consistency and improving accuracy in the selection of partitioning properties from literature sources. First, we show that a widely used procedure does not always minimize the adjustments of property values derived from the literature when harmonizing them according to thermodynamic constraints. In such cases, the final adjusted values (FAVs) are unnecessarily different from the literature-derived values (LDVs) selected from measurements. We present an improved procedure based on the theory of least squares that minimizes the adjustment of LDVs and allows quantitative propagation of uncertainty from LDVs to FAVs. When this procedure is applied to partitioning properties for 30 organic chemicals, FAVs obtained differ by up to 30% from those calculated with the current adjustment procedure. Second, we point out that the adjustment procedure is only appropriate for correcting random errors in measurement data. Biased LDVs must be identified and corrected prior to harmonization. Using a set of 16 PCB congeners as a case study, we provide methods to identify biased data and discuss possible sources of bias. We present a new interpretation of property data for the PCBs and a new set of internally consistent properties and quantitative structure-property relationships that we recommend as the best currently available.

We have developed and illustrated a general regional multi-species model that describes the fate and transport of mercury in three forms, elemental, divalent, and methylated, in a generic regional environment including air, soil, vegetation, water, and sediment. The objectives of the model are to describe the fate of the three forms of mercury in the environment and to determine the dominant physical sinks that remove mercury from the system. Chemical transformations between the three groups of mercury species are modeled by assuming constant ratios of species concentrations in individual environmental media. We illustrate and evaluate the model with an application to describe the fate and transport of mercury in the San Francisco Bay Area of California. The model successfully rationalizes the identified sources with observed concentrations of total mercury and methyl mercury in the San Francisco Bay Estuary. The mass balance provided by the model indicates that continental and global background sources control mercury concentrations in the atmosphere but that loadings to water in the San Francisco Bay Estuary are dominated by runoff from the Central Valley catchment and remobilization of contaminated sediments deposited during past mining activities. The model suggests that the response time of mercury concentrations in the San Francisco Bay Estuary to changes in loadings is long, on the order of 50 years.

We introduce a new global-scale multimedia contaminant fate model (the Berkeley-Trent Global Model; BETR-Global) that integrates global climate data from the National Centers for Environmental Prediction (NCEP). BETR-Global represents the global environment as a connected set of 288 multimedia regions on a 150 grid. We evaluate the model by simulating the global fate and transport of seven PCB congeners over a 70 year period and find satisfactory agreement between model output and observations of atmospheric PCB concentrations at 11 long-term monitoring stations in the Northern Hemisphere. We demonstrate the use of the model as a tool for understanding global pollutant dynamics by examining the hypothesis that variability in global-scale climate conditions, as reflected by the North Atlantic Oscillation (NAO), influences atmospheric PCB concentrations in the Northern Hemisphere. We estimate that the maximum variability in atmospheric PCB concentrations attributable to NAO variability is approximately a factor of 2. The influence of variability in the NAO on PCB concentrations in air is most likely to be observed in the winter and spring at monitoring sites in Northern Europe and the Arctic. Analysis of long-term monitoring data from 11 sites shows some statistically significant relationships between NAO indices and atmospheric PCB concentrations during the winter and spring. Giving consideration to competing factors that influence atmospheric PCB concentrations, longer time series of monitoring data are required to fully evaluate the modeling results and to improve our understanding of the role of climate variability on the long-term fate of persistent semivolatile pollutants.

Overall persistence (P-ov) and long-range transport potential (LRTP) of organic chemicals are environmental hazard metrics calculated with multimedia fate and transport models. Since there are several models of this type, it is important to know whether and how different model designs (model geometry, selection of compartments and processes, process descriptions) affect the results for P., and LRTP. Using a set of 3175 hypothetical chemicals covering a broad range of partition coefficients and degradation half-lives, we systematically analyze the P-ov and LRTP results obtained with nine multimedia models. We have developed several methods that make it possible to visualize the model results efficiently and to relate differences in model results to mechanistic differences between models. Rankings of the hypothetical chemicals according to P-ov and LRTP are highly correlated among models and are largely determined by the chemical properties. Domains of chemical properties in which model differences lead to different results are identified, and guidance on model selection is provided for model users.

The Berkeley-Trent (BETR)-World model, a 25 compartment, geographically explicit fugacity-based model is described and applied to evaluate the transport of chemicals from temperate source regions to receptor regions (such as the Arctic). The model was parameterized using GIS and an array of digital data on weather, oceans, freshwater, vegetation and geo-political boundaries. This version of the BETR model framework includes modification of atmospheric degradation rates by seasonally variable hydroxyl radical concentrations and temperature. Degradation rates in all other compartments vary with seasonally changing temperature. Deposition to the deep ocean has been included as a loss mechanism. A case study was undertaken for alpha-HCH. Dynamic emission scenarios were estimated for each of the 25 regions. Predicted environmental concentrations showed good agreement with measured values for the northern regions in air, and fresh and oceanic water and with the results from a previous model of global chemical fate. Potential for long-range transport and deposition to the Arctic region was assessed using a Transfer Efficiency combined with estimated emissions. European regions and the Orient including China have a high potential to contribute alpha-HCH contamination in the Arctic due to high rates of emission in these regions despite low Transfer Efficiencies. Sensitivity analyses reveal that the performance and reliability of the model is strongly influenced by parameters controlling degradation rates. (C) 2003 Elsevier Ltd. All rights reserved.

Transfer efficiency (TE) is introduced as a model output that can be used to characterize the relative ability of chemicals to be transported in the environment and deposited to specific target ecosystems. We illustrate this concept by applying the Berkeley-Trent North American contaminant fate model (BETR North America) to identify organic chemicals with properties that result in efficient atmospheric transport and deposition to the Laurentian Great Lakes. By systematically applying the model to hypothetical organic chemicals that span a wide range of environmental partitioning properties, we identify combinations of properties that favor efficient transport and deposition to the Lakes. Five classes of chemicals are identified based on dominant transport and deposition pathways, and specific examples of chemicals in each class are identified and discussed. The role of vegetation in scavenging chemicals from the atmosphere is assessed, and found to have a negligible influence on transfer efficiency to the Great Lakes. Results indicate chemicals with octanol-water (K-ow) and air-water (K-aw) partition coefficients in the range of 10(5)-10(7) and 10(-4)-10(-1) combine efficient transport and deposition to the Great Lakes with potential for biaccumulation in the aquatic food web once they are deposited. A method of estimating the time scale for atmospheric transport and deposition process is suggested, and the effects of degrading reactions in the atmosphere and meteorological conditions on transport efficiency of different classes of chemicals are discussed. In total, this approach provides a method of identifying chemicals that are subject to long-range transport and deposition to specific target ecosystems as a result of their partitioning and persistence characteristics. Supported by an appropriate contaminant fate model, the approach can be applied to any target ecosystem of concern. (C) 2003 Elsevier Ltd. All rights reserved.

Mass balance models of chemical fate and transport can be applied in ecological risk assessments for quantitative estimation of concentrations in air, water, soil, and sediment. These concentrations can, in turn, be used to estimate organism exposures and ultimately internal tissue concentrations that can be compared to mode-of-action-based critical body residues that induce toxic effects. From this comparison, risks to the exposed organism can be evaluated. To demonstrate the use of fate models in ecological risk assessment, we combine the EQuilibrium Criterion (EQC) environmental fate model with a simple screening level biouptake model for three representative organisms: a bird, a mammal, and a fish. This effort yields estimates of internal body concentrations that can be compared with levels known to elicit toxic effects. As an illustration, we present an analysis of 24 hydrocarbon components of gasoline that differ in properties but are assumed to elicit toxicity by a common narcotic mode of action, Results demonstrate that differences in chemical properties and mode of entry into the environment lead to profound differences in the efficiency of transport from emission to target biota. We discuss the implications of these results and draw attention to the insights gained about regional fate and ecological risks associated with gasoline. This approach is suitable for assessing single chemicals or mixtures that have similar modes of action. We conclude that the model-based methodologies presented are widely applicable for screening level ecological risk assessments that support effective chemicals management.