Source model, hybrid

Three generic types of receptor model have been identified, chemical mass balance, multivariate, and microscopical identification. Each one has certain requirements for input data to provide a specified output. An approach which combines receptor and source models, source/ receptor model hybridization, has also been proposed, but it needs further study. 

Receptor models presently in use can be classified into one of four categories chemical mass balance, multivariate, microscopic, and source/receptor hybrids. Each classification will be treated individually, though it will become apparent that they are closely related. 

Hybrid Source/Receptor Models. Until now, the receptor models have been treated as if they were completely separate entities from the source models. This need not be the case. 

A source model incorporates measured or estimated values for an emission rate factor and the dispersion factor. Whenever either of these enter the receptor model as observables, we call it a hybrid model. The three applications considered here are emission inventory scaling, micro-inventories, and dispersion modeling of specific sources within a source type. 

Two more sets of observables are Introduced Into the hybrid models the emissions factors and the dispersion factors. It Is the difficulty of quantifying these that led to the use of a receptor model over the source model In the first place, so It would seem there Is little advantage In reintroducing them. The advantage of the hybridization Is that the number of Individual emission and dispersion factors can be considerably reduced and that the relative values rather than the absolute values are used. These relative values are more accurate In most cases. Still, the uncertainties of emission and dispersion factors need to be evaluated and Incorporated Into any source/receptor hybrid model. 

Source Characterization. All receptor models, even the source/receptor hybrids, require input data about the particulate matter sources. The multivariate models, which can conceivably be used to better estimate source compositions, require an initial knowledge of the chemical species associations in sources. 

Source Finding Hybrid Receptor Model (Yamartino). The starting point of this model (5) is a iet of equations of the form... 

Dincer I (2010) Economic and environmental comparison of conventional and alternative vehicle options, hr Pistoia G (ed) Electric and hybrid vehicles— power sources, models, sustainability, infrastructure and the market Elsevira, Amsterdam... 

D. Friel, in G. Pistoia (Ed.), Electric and Hybrid Vehicles Power Sources, Models, Sustainability, Infrastructure and the Market, Elsevier B. V., 2010. Ch. 19. 

Next we consider the compact star in the low mass X-ray binary 4U 1728-34. In a very recent paper Shaposhnikov et al. (2003) (hereafter STH) have analyzed a set of 26 Type-I X-ray bursts for this source. The data were collected by the Proportional Counter Array on board of the Rossi X-ray Timing Explorer (RXTE) satellite. For the interpretation of these observational data Shaposhnikov et al. 2003 used a model of the X-ray burst spectral formation developed by Titarchuk (1994) and Shaposhnikov Titarchuk (2002). Within this model, STH were able to extract very stringent constrain on the radius and the mass of the compact star in this bursting source. The radius and mass for 4U 1728-34, extracted by STH for different best-fits of the burst data, are depicted in Fig. 6 by the filled squares. Each of the four MR points is relative to a different value of the distance to the source (d = 4.0, 4.25, 4.50, 4.75 kpc, for the fit which produces the smallest values of the mass, up to the one which gives the largest mass). The error bars on each point represent the error contour for 90% confidence level. It has been pointed out (Bombaci 2003) that the semi-empirical MR relation for the compact star in 4U 1728-34 obtained by STH is not compatible with models pure hadronic stars, while it is consistent with strange stars or hybrid stars. 

Stiller C., Thorud B., Scljcbo S., Mathisen 0., Karoliussen H., Bolland O. (2005) Finite-volume modeling and hybrid-cycle performance of planar and tubular solid oxide fuel cells. Journal of Power Sources 141, 227-240. 

Han, Y.-J., Holsen, T.M., Hopke, P.K., Cheong, J.-P., Kim, H., Yi, S.-M., 2002. Identification of source locations for atmospheric dry deposition of heavy metals during yellow-sand events in Seoul, Korea in 1998 using hybrid receptor models. Atmos. Environ. 38, 5353-5361. 

The one-center energy components have no clear correspondence in the standard MM setting. In our approach the one-center contributions E- arise due to deviations of the geminal amplitude related ES Vs (7>P and 41 ) from their transferable values. These deviations interfere with hybridization. The derivatives of E f s with respect to the angles Land uji, taken at the values characteristic for the stable hybridization tetrahedra shapes which appear in the FATO model, yield quasi- and pseudotorques acting upon the hybridization tetrahedron. In evaluating these quantities we notice that all the hybridization dependence which appears in the one-center terms is that of the matrix elements of eq. (2.71). In the latter, the only source of the hybridization dependence is that of the second and fourth powers of the coefficients of the s-orbital in the HOs. Since they do not depend on the orientation of the hybridization tetrahedra, we immediately arrive at the conclusion that no quasitorques caused by the variation of electron densities appear in the TATO setting ... 

To cope with the problems of a mechanistic description of CC, we will first analyze three basic questions the nature of the differences in behavior between central atoms on the one hand and organogenic atoms on the other hand, which results in limitations for the MM techniques when applied to molecules of CC. Getting an idea of the source of these differences tentatively allows us to address further questions developing an adequate MM-like scheme for CCs of nontransition metals and non-metals which will be able to reproduce fine structural features of the mutual ligand influence characteristic for this class of molecules. Next we turn to the most complex problem - developing a hybrid modeling technique which would allow us to cover complexes of transition metals with open 7-shells. 

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