The Interpretation Phase

The interpretation phase consists of three elements identification of significant issues, evaluation by various checks and conclusions, and giving recommendations and reporting (Fig. 15.5). 

The third phase contains the conclusions, the recommendations, and the presentation of results. The relation between the interpretation phase and the other phases of LCA are illustrated in Fig. 5. 

The previous two phases - inventory and impact assessment - represent the domain of expertise of LCA. Indeed, the approach here is very technical, and the data voluminous. In the interpretation phase of LCA, it is the user, the responsible party, the decision maker, who uses the results of the impact assessment in order to determine the main actions to be taken, which must take other dimensions (research and development, marketing, production, finance, etc.) into consideration. 

The interpretation phase of a carbon footprint study is a time to formally reflect on the meaning of outcomes of the preceding three steps, and probably to do parts of them again. This iterativeness is the symbolic intent of the double arrows in Figure 1.1 — in fact at any step in the overall process the analyst will frequently learn about the effect of decisions made in the other steps, which may point out inconsistencies that need to be removed or opportunities for product improvement that deserve consideration in additional scenarios. 

The standard ISO 14043 divides the interpretation phase into three sections ... 

An LCA study completes with the interpretation phase, where the overall process is evaluated, the results obtained from previously completed phases (i.e., LCI and LCIA) are reported, and overall conclusions and recommendations are drawn and made, respectively. According to ISO 14040 (ISO, 2006a,b), the interpretation shall clarify that the results of the LCIA indicate potential environmental effects, but they do not predict actual impact on specific impact categories. 

A consistency check is necessary at the beginning of the interpretation phase in order to determine whether the assumptions, methods, models, and data applied in the analysis are consistent with the goal and scope of die smdy. A completeness check is also deemed necessary in this phase to ensure that all relevant information and data needed for the interpretation phase are available and complete. The contribution analysis that follows aims to indicate the contribution of specific flows, processes, or impacts to the results. The interpretation phase may include the perturbation analysis, where the effects of small changes within the system on the results of an LCA are evaluated. In the last step of the interpretation phase, conclusions and recommendations based on the results obtained from previous phases of the LCA are documented (Guinee, 2002). 

The first system called LiSSA has been developed for interpretation of data from eddy-current inspection of heat exchangers. The data that has to be interpreted consists of a complex impedance signal which can be absolute and/or differential and may be acquired in several frequencies. The interpretation of data is done on the basis of the plot of the signal in the impedance plane the type of defect and/or construction is inferred from the signal shape, the depth from the phase, and the volume is roughly proportional to the signal amplitude. 

The computed CWT leads to complex coefficients. Therefore total information provided by the transform needs a double representation (modulus and phase). However, as the representation in the time-frequency plane of the phase of the CWT is generally quite difficult to interpret, we shall focus on the modulus of the CWT. Furthermore, it is known that the square modulus of the transform, CWT(s(t)) I corresponds to a distribution of the energy of s(t) in the time frequency plane [4], This property enhances the interpretability of the analysis. Indeed, each pattern formed in the representation can be understood as a part of the signal s total energy. This representation is called "scalogram". 

Figure Al.6.7. Schematic diagram illustrating the different possibilities of interference between a pair of wavepackets, as described in the text. The diagram illustrates the role of phase ((a) and (c)), as well as the role of time delay (b). These cases provide the interpretation for the experimental results shown in figure Al.6.8. Reprinted from [22],...

Flere, we shall concentrate on basic approaches which lie at the foundations of the most widely used models. Simplified collision theories for bimolecular reactions are frequently used for the interpretation of experimental gas-phase kinetic data. The general transition state theory of elementary reactions fomis the starting point of many more elaborate versions of quasi-equilibrium theories of chemical reaction kinetics [27, M, 37 and 38]. 

Several alternative attempts have been made to quantify Lewis-acid Lewis-base interaction. In view of the HSAB theory, the applicability of a scale which describes Lewis acidity with only one parameter will be unavoidably restricted to a narrow range of struchirally related Lewis bases. The use of more than one parameter results in relationships with a more general validity ". However, a quantitative prediction of the gas-phase stabilities of Lewis-acid Lewis-base complexes is still difficult. Hence the interpretation, not to mention the prediction, of solvent effects on Lewis-add Lewis-base interactions remains largely speculative. 

At elevated temperatures (250-400°C) bromine reacts with thiazole in the vapor phase on pumice to afford 2-bromothiazole when equimolecu-lar quantities of reactants are mixed, and a low yield of a dibromothiazole (the 2,5-isomer) when 2 moles of bromine are used (388-390). This preferential orientation to the 2-position has been interpreted as an indication of the free-radical nature of the reaction (343), a conclusion that is in agreement with the free-valence distribution calculated in the early application of the HMO method to thiazole (Scheme 67) (6,117). 

To increase the number of theoretical plates without increasing the length of the column, it is necessary to decrease one or more of the terms in equation 12.27 or equation 12.28. The easiest way to accomplish this is by adjusting the velocity of the mobile phase. At a low mobile-phase velocity, column efficiency is limited by longitudinal diffusion, whereas at higher velocities efficiency is limited by the two mass transfer terms. As shown in Figure 12.15 (which is interpreted in terms of equation 12.28), the optimum mobile-phase velocity corresponds to a minimum in a plot of H as a function of u. 

Powder diffraction patterns have three main features that can be measured t5 -spacings, peak intensities, and peak shapes. Because these patterns ate a characteristic fingerprint for each crystalline phase, a computer can quickly compare the measured pattern with a standard pattern from its database and recommend the best match. Whereas the measurement of t5 -spacings is quite straightforward, the determination of peak intensities can be influenced by sample preparation. Any preferred orientation, or presence of several larger crystals in the sample, makes the interpretation of the intensity data difficult. 

The fluidity of coal increases and then decreases at a given temperature. This has been interpreted in terms of reaction sequence of coal — fluid coal — semicoke. In the initial step, a part of the coal is decomposed to add to that which normally becomes fluid. In the second step, the fluid phase decomposes to volatile matter and a soHd semicoke. The semicoke later fuses accompanied by evolution of additional volatile matter to form a high temperature coke. 

Kinetic investigations of alkylchlorodiazirine thermolysis were carried out in the gas phase 70JCS(A)1916). Chloromethyldiazirine (232) decomposition follows first order kinetics giving nitrogen and vinyl chloride, easily interpretable as isomerization of a carbene. 

Numerical values for solid diffusivities D,j in adsorbents are sparse and disperse. Moreover, they may be strongly dependent on the adsorbed phase concentration of solute. Hence, locally conducted experiments and interpretation must be used to a great extent. Summaries of available data for surface diffusivities in activated carbon and other adsorbent materials and for micropore diffusivities in zeolites are given in Ruthven, Yang, Suzuki, and Karger and Ruthven (gen. refs.). 

The prediction of drop sizes in liquid-liquid systems is difficult. Most of the studies have used very pure fluids as two of the immiscible liquids, and in industrial practice there almost always are other chemicals that are surface-active to some degree and make the pre-dic tion of absolute drop sizes veiy difficult. In addition, techniques to measure drop sizes in experimental studies have all types of experimental and interpretation variations and difficulties so that many of the equations and correlations in the literature give contradictoiy results under similar conditions. Experimental difficulties include dispersion and coalescence effects, difficulty of measuring ac tual drop size, the effect of visual or photographic studies on where in the tank you can make these obseiwations, and the difficulty of using probes that measure bubble size or bubble area by hght or other sample transmission techniques which are veiy sensitive to the concentration of the dispersed phase and often are used in veiy dilute solutions. 

The activity of antioxidants in food [ 1 ] emulsions and in some biological systems [2] is depends on a multitude of factors including the localisation of the antioxidant in the different phases of the system. The aim of this study is determining antioxidant distributions in model food emulsions. For the purpose, we measured electrochemically the rate constant of hexadecylbenzenediazonium tetrafluorborate (16-ArN,BF ) with the antioxidant, and applied the pseudophase kinetic model to interpret the results. 

The observed acidities in the gas phase are interpreted in terms of the negative induction effect of the halo substituents however, the microscopic picture of the solvent effects in addition to such induction effects of the solute have not been clarified. 

Molecular dynamics simulations have also been used to interpret phase behavior of DNA as a function of temperature. From a series of simulations on a fully solvated DNA hex-amer duplex at temperatures ranging from 20 to 340 K, a glass transition was observed at 220-230 K in the dynamics of the DNA, as reflected in the RMS positional fluctuations of all the DNA atoms [88]. The effect was correlated with the number of hydrogen bonds between DNA and solvent, which had its maximum at the glass transition. Similar transitions have also been found in proteins. 

The amplitudes and the phases of the diffraction data from the protein crystals are used to calculate an electron-density map of the repeating unit of the crystal. This map then has to be interpreted as a polypeptide chain with a particular amino acid sequence. The interpretation of the electron-density map is complicated by several limitations of the data. First of all, the map itself contains errors, mainly due to errors in the phase angles. In addition, the quality of the map depends on the resolution of the diffraction data, which in turn depends on how well-ordered the crystals are. This directly influences the image that can be produced. The resolution is measured in A... 

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