Assessing Alternative Environmental Scenarios

Without any changes to the production network, the operating cash flows and the NPV of the network would be reduced by approximately 10% in comparison to the baseline values. However, by re-allocating production volumes within existing capacities, it is possible to restore previously earned operating cash flows. To do so, production volumes are shifted to the major site A, which is located in the Euro zone. Contrarily, site C, which is located in the USA, would not be utilized at all by the product groups included in the example. It should be noted that this does not imply a closure of the US site since only a subset of the product portfolio was included in the analysis. The net present value of the network is nevertheless affected by the US appreciation because of the restructuring costs associated with the re-allocation of production volumes. 

Operating cash flows with US appreciation to 2001 level and no network changes 

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Estimating distance. For both the worst-case and alternative release scenario, the source must estimate the distance to where the endpoint is no longer exceeded, and estimate the population (rounded to two significant digits) within a circle defined by the distance and centered at the release point. U.S. Census data may be used and does not have to be updated. However, the presence of sensitive populations (e.g., hospitals, schools, etc.) must be noted. The source must identify and list the types of environmental receptors within the calculated worst-case distance and circle, but no environmental damage assessment is required. In determining the presence of environmental receptors, U.S. Geological Survey maps may be used. 

The size and quality of the available database for an environmental pollutant will vary greatly across substances and will also vary within the four components of the typical risk assessment. The variety of adverse health risks of a substance may be qualitatively well known, for example, but dose—response relationships may be poorly quantifiable because of either limits of inadequate exposure measurement data or absence of good biomarkers of adverse effect or absence of information on the full span of the dose—response curve. Hazard characterization and dose—response relationships may both be understood as general descriptors, but case-specific or scenario-specific exposure data may be lacking, requiring judgment about alternative approaches (e.g., default values). 

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