Risk matrix limitations

Risk indices are single numbers or a tabulation of numbers that are correlated to the magnitude of the risk to people. Some risk indices are relative values with no specific units. The limitations on the use of indices are that they may not be an absolute criteria for accepting or rejecting the risk. Risk indices also do not communicate the same information as individual or societal risk measures. An example of risk indices is a risk ranking matrix. Table 6-4 (modified from CCPS, 1992) shows how severity and likelihood are combined to obtain risk indices. An example risk matrix is shown in Figure 6-3 (RRS, 2002). 

We can now see that the components can be assigned to certain quadrants in the risk matrix. It can be easily derived that Component 1 has the highest impact and the highest likelihood of all components. On the other hand Component 2 has the lowest impact and lowest likelihood (together with Component 3). As we all have limited test resources in our project we need to make choices as to what should be... 

Here, risk levels also can be defined as discussed previously, but in the reverse manner. Here, the top left part of the matrix is the highest risk area, whereas the bottom right part is lowest risk. There is no upper and lower limit. Too much increase/ decrease of in the categories of risk frequency or consequence, has no practical value really. So, in practice, these are restricted to 3 x3 or 5 x5 matrix, which need not be a square matrix as is evident from the above (6x4). Table 1/3.3.2-6 is an example of 4x4 semi-quantitative risk matrix. 

As risk matrix application is wide it is extremely important to determine right at the initial stage, which consequence is of interest in the current program. These consequence lists shall include but are not limited to the following ... 

The risk matrix method can provide a quick understanding of the risk profile of the facility and can be based on judgment or be further investigated using more detailed information. This method has limitations also. It is not easy to incorporate the effects of risk reduction measures within the risk matrix, and it cannot be used for cumulative risks. 

Although we have described powder metallurgy as being an ideal process, without limitations or hazards, it does pose some serious safety risks and limitations. The majority of metallic powders and other finely divided solids are pyrophoric, meaning that they will spontaneously ignite in air at temperatures below 55°C. Unlike black powder, which contains both the fuel (C and S) and oxidizer (potassium nitrate), it is not immediately apparent why metallic powders would ignite, since both key components are not present within the powder matrix. 

Vapor-phase monitoring to meet the 3X specification will most likely not be sufficient to verify agent destruction in the solid materials from the bulk sites because these materials could contain either strongly adsorbed agent or occluded agent that could be released in the future. Because of the unique analytical interferences resulting from the composition of particular waste streams, the measurement methods will have to be specific to each waste stream, and each method will have to be validated for the specific waste matrix. Criteria for determining the detection limit for each method should be based on the hazard and risk evaluations for that waste stream. 

These tools should not be considered limited in application to the initial validation effort. By keeping the traceability matrix up to date it becomes (and will remain) an important tool for assessing the impact of changes to the database, and both it and the risk assessment process are still important test planning tools as part of change control. Of course, sound change control practices are absolutely imperative for keeping an application validated. 

However, for a given element and matrix, it is possible to enhance the resolution by working at a low accelerating voltage (L or M lines). Under these circumstances resolutions of around 0.2 to 0.5 pm can be obtained. There are, however, two limitations when adopting such conditions on the one hand, the intensity of the L or M lines is less than that of the K lines (the detection limits are thus higher) and, on the other hand, there is a risk of the low... 

Factor VII is the most sensitive of the vitamin K-dependent clotting factors. The mode of action is tissue factor-dependent activation of factors Xa and IXa on the surfaces of activated platelets (1). Factor Xa leads to thrombin generation and hemostasis, by converting fibrinogen to fibrin. This process is limited to the site of injury, since exposure of tissue factor from the subendothelial matrix has a role in the action of recombinant factor Vila, thereby reducing the risk of thromboembohc events (2). 

The constancy of the nebulizer gas flow is of prime importance for the precision achievable in ICP-MS. After stabilizing the nebulizer gas flows, relative standard deviations can be below 1%. They can be improved still further by internal standardization [509]. The tolerable salt concentrations (1-5 g/L) are much lower than in ICP-AES, because of the risks of sampler clogging and depend on the respective salts. The memory effects may become limiting and in the case of a high matrix load rinsing times of 1-2 min are required. 

Thus, to reduce the risk of dissolution rate-limited bioavailability, and if there is sufficient compound, grinding in a mortar and pestle should be done to reduce the particle size of the compound. If larger quantities are available, then ball milling or micronization can be used to reduce the particle size. The main methods of particle size reduction have been reviewed by Spencer and Dalder (1997), who devised the mill selection matrix shown in Table 6.1. 

Although certainly not limited to matrix models, the data used to construct models are often developed in the laboratory where the organisms have been cultured under optimal conditions. Hence, fecundity is often overestimated and mortality is underestimated. This is not an issue when comparing different life histories when all species have been raised under the same conditions, but can result in erroneous conclusions if the model is used for a risk assessment of a specific species in the wild. Thus, field-collected data are essential when trying to protect endangered species. 

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