Assessment factors model ecosystem

In aquatic risk assessment, an important question at stake is how unique model ecosystem experiments are in their threshold concentrations for direct toxic effects. When comparing chemicals for which at least 5 aquatic NOECeco values are available, it appears that geographical extrapolation of model ecosystem experiments is possible. The proposed geographical uncertainty factor (spread) for threshold concentrations was in the range of 1.4 to 5.4 (Section 7.2.5). 

Model ecosystem data with small assessment factor... 

It is desirable to assess whether a proposed aquatic EQS is accurate in terms of the known impacts of the chemical in the real world. This can be done by comparing the EQS with suitable model ecosystem data (if these were not used in its derivation) or better still by inspection of appropriate field data, particularly from pollution gradients for which the presence of any confounding factors (e.g., other chemicals) is well understood. 

Assessment factors, whose size should be designed to reflect expected uncertainties in the data, should generally be used when deriving EQS values from either laboratory or model ecosystem data. It may also be appropriate to apply small assessment factors to the outcome of SSDs. 

Ultimately a derived no-effect level (DNEL) (in humans) or a predicted no-effect concentration (PNEC)20 (in ecosystems) is calculated for a substance, group of substances or chemical mixture. Assessment factors (AF) - sometimes referred to as uncertainty factors or safety factors - compensate for lack of data and assumptions resulting from dose spacing and other test model parameters (adapted from [124]) ... 

The Predicted No Effect Concentration may be derived from laboratory, field or theoretical data. Studies conducted on single species such as acute toxicity to fish (IX so) over a relatively short time scale (normally 40 or % h) and with death as the only recorded endpoint is, by itself, only of limited value in deciding whether or not a predicted environmental level of a dye is, or, is not, acceptable. Extrapolation from acute effects to chronic and ecosystems effects involves numerous uncertainties. In order to protect the ecosystem, conservative assessment factors have been introduced based on the statistical analysis of a set of data [17] for chronic exposure. The US-EPA [18] has proposed to apply a factor of KXX) for a single acute L(E)Cso value or 100 to the lowest value if all 3 tests are available (fish, daphniae, algae). These models have in common that they assume steady state concentrations in the aquatic environment. 

In this context it is important to improve the analysis of the extent to which sensitive organisms and ecosystems in such areas may need specific test methods and specific concern in environmental risk assessment of chemicals (Breitholtz et al. 2006a). In the future, it is therefore important to increase research efforts to elucidate potential consequences of varying physical and chemical environmental factors for toxicity of a wide range of chemical substances, in order to develop tools for hazard identification and dose-response assessment that include scientifically well-based combinations of species, endpoints and environmental factors. The battery of endpoints to select from should, as far as possible, comprise population level data (Forbes and Calow 1999, Forbes et al. 2001, Breitholtz et al. 2006a), possibly obtained by using population models. 

Few studies have been carried out on the fate of pesticides in tropical ecosystems. If reported, they often lack an appropriate assessment of the processes that affect fate and factors influencing those processes imder specific conditions. Due to the complexity of the environmental problems, modeling is seen as an essential tool in resolving them. 

Scientists have developed computer models that depict the physical, chemical and biological processes within forest watersheds. Watershed acidification models can be used as research and management tools to investigate factors responsible for the historical acidification of soil and water as well as the ecosystem response to anticipated future changes in acidic deposition. In order to effectively predict the pH, ANC and aluminum concentrations in streams, all major chemicals must be accurately simulated (e.g., sulfate, nitrate, calcium, magnesium). The acidification model PnET-BGC was used for this assessment because it has been rigorously tested at Hubbard Brook and other sites in the northeastern United States, and it allows the user of the model to consider the ecosystem response to multiple chemicals simultaneously. Other frequently used acidification models include MAGIC (Cosby et al. 2001), and NuCM (Lui et al. 1992). 

Even the most sophisticated risk assessment has limitations. It involves numerous assumptions about both exposure and hazard. Exposure assessments typically reflect modeled concentrations or extrapolations from measured data. The degree of exposure by different individuals may vary, and their response can depend on factors such as general health, genetic predisposition, or other factors. Dose-response factors are typically extrapolated from animal studies and thus inherently introduce the imcertainty of relating the response of laboratory animals to that of humans or one of the many species in an ecosystem. The endpoints characterized may not include all of the potential effects for example, the potential for endocrine disruption has not been considered in many risk assessments and in fact standardized testing methods were not published until approximately 2007 or later [90]. And risk assessment tools only model relatively simple scenarios. They rarely account for exposure to multiple chemicals, or fully accoimt for the effects on a complex web of organisms in an ecosystem. 

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