Evaluating and Ranking the Options

A variety of factors and methods were used to evaluate and rank the twelve options. For example, the study team considered the reduction in relative risk to human health achieved by different options. Generally, an option s effectiveness in reducing health risks was evaluated by calculating its effect on exposure to benzene emissions. The study team selected benzene emissions as an indicator because benzene can be found in all waste media (air, water, groundwater, and surface water) and poses a known threat to human health. 

Thirteen other factors were also considered in evaluating each option (1) capital costs, (2) operating and maintenance costs, (3) liability cost rating, (4) timeliness, (5) transferability, (6) revenues, (7) equivalent annual costs, (8) pollution prevention mode, (9) net release reduction, (10) recovery costs, (11) cost effectiveness, (12) resource utilization, and (13) effects of secondary emissions. Finally, data Ifom public opinion polling in the community near the refinery were considered in evaluating potential public support or opposition to different pollution prevention strategies. 

When reducing benzene emissions was considered to be the primary goal, the study team calculated that six high-ranked options together reduced benzene exposure by 90% at an annual cost of 4.5 million. This was only 20% of the annual cost of all the options mandated by regulation. 

The study team examined current obstacles to and incentives for implementing five of the highly ranked options. At least three major obstacles were identified (1) limited resources, (2) poor economic return, and (3) regulatory disincentives. Ifie study team concluded that these obstacles create a formidable constraint on implementing pollution prevention strategies that go beyond current regulatory requirements. 

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Developing a system for evaluating and ranking the options in light of cost, risk, regulatory requirements, and other factors. 

Whereas the criteria (i) enantioselectivity, (ii) amount of product obtained per amount of catalyst used, and (iv) substrate specificity are of a quantitative nature, the point (iii) availability (though not cost) of a catalyst is only a semi-quantita-tive criterion, and (v) comparison of a method with alternative strategies is even redundant, as the process of comparison of options and their resulting evaluation and ranking are merely different parts of the decision-making process, and are not undertaken in parallel with performance measurements along dimensions of merit. 

Determine investment required for each waste reduction option Determine financial attractiveness of each option and rank options Evaluate the environmental impacts of each option ... 

Parallel relations of options in both diagrams, such as < <, > > and —. E.g., the parallel relation < < means that scenario x < scenario y in HD1 and scenario x < scenario y in HD2. Parallel order relations indicate a similar ranking of options in the two compared Hasse Diagrams and thus there is no evaluation conflict. 

In summary, computational quantum mechanics has reached such a state that its use in chemical kinetics is possible. However, since these methods still are at various stages of development, their routine and direct use without carefully evaluating the reasonableness of predictions must be avoided. Since ab initio methods presently are far too expensive from the computational point of view, and still require the application of empirical corrections, semiempirical quantum chemical methods represent the most accessible option in chemical reaction engineering today. One productive approach is to use semiempirical methods to build systematically the necessary thermochemical and kinetic-parameter data bases for mechanism development. Following this, the mechanism would be subjected to sensitivity and reaction path analyses for the determination of the rank-order of importance of reactions. Important reactions and species can then be studied with greatest scrutiny using rigorous ab initio calculations, as well as by experiments. 

Based on the MAC economic model approach and assumptions outlined above, the MAC figures were estimated for each short-listed opportunity evaluated. Table 5 presents a summary of the top six opportunities rank-ordered by cost savings / OPEX and C02e reductiorr (three additional options provided for informatiorr orrly). Significant cost and GHG emissions savings can be seen within these projects. 

Despite the hmitations, the model provides an indication of the worst networks nodes in terms of security of supply and provides their numerical ranking. It is recommended to use the results of the model in a qualitative (comparative) way rather than interpret numerical values directly. The model is very powerful to compare and evaluate different supply options, new network development plans and analyse potential crisis situations. 

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