Pollutant emissions during pyrolysis and combustion of waste printed circuit boards, before and after metal removal

The constant increase in the production of electronic devices implies the need for an appropriate management of a growing number of waste electrical and electronic equipment. Thermal treatments represent an interesting alternative to recycle this kind of waste, but particular attention has to be paid to the potential emissions of toxic by-products. In this study, the emissions from thermal degradation of printed circuit boards (with and without metals) have been studied using a laboratory scale reactor, under oxidizing and inert atmosphere at 600 and 850 °C. Apart from carbon oxides, HBr was the main decomposition product, followed by high amounts of methane, ethylene, propylene, phenol and benzene. The maximum formation of PAHs was found in pyrolysis at 850 °C, naphthalene being the most abundant. High levels of 2-, 4-, 2,4-, 2,6- and 2,4,6-bromophenols were found, especially at 600 °C. Emissions of PCDD/Fs and dioxin-like PCBs were quite low and much lower than that of PBDD/Fs, due to the higher bromine content of the samples. Combustion at 600 °C was the run with the highest PBDD/F formation: the total content of eleven 2,3,7,8-substituted congeners (tetra- through heptaBDD/Fs) was 7240 and 3250 ng WHO2005-TEQ/kg sample, corresponding to the sample with and without metals, respectively.

Saint Mathew Law and Bonini Paradox in Textual Theory of Complex Models

The mathematical models of the complex reality are texts belonging to a certain literature that is written in a semi-formal language, denominated L(MT) by the authors whose laws linguistic mathematics have been previously defined. This text possesses linguistic entropy that is the reflection of the physical entropy of the processes of real world that said text describes. Through the temperature of information defined by Mandelbrot, the authors begin a text-reality thermodynamic theory that drives to the existence of information attractors, or highly structured point, settling down a heterogeneity of the space text, the same one that of ontologic space, completing the well-known law of Saint Mathew, of the General Theory of Systems and formulated by Margalef saying: “To the one that has more he will be given, and to the one that doesn't have he will even be removed it little that it possesses.

Chebanov law and Vakar formula in mathematical models of complex systems

Ecological models written in a mathematical language L(M) or model language, with a given style or methodology can be considered as a text. It is possible to apply statistical linguistic laws and the experimental results demonstrate that the behaviour of a mathematical model is the same of any literary text of any natural language. A text has the following characteristics: (a) the variables, its transformed functions and parameters are the lexic units or LUN of ecological models; (b) the syllables are constituted by a LUN, or a chain of them, separated by operating or ordering LUNs; (c) the flow equations are words; and (d) the distribution of words (LUM and CLUN) according to their lengths is based on a Poisson distribution, the Chebanov's law. It is founded on Vakar's formula, that is calculated likewise the linguistic entropy for L(M). We will apply these ideas over practical examples using MARIOLA model. In this paper it will be studied the problem of the lengths of the simple lexic units composed lexic units and words of text models, expressing these lengths in number of the primitive symbols, and syllables. The use of these linguistic laws renders it possible to indicate the degree of information given by an ecological model.

The conversation on political issues on Twitter: an analysis of the participation and frames in the debate on the 'Wert law' and evictions in Spain

The aim of this study is to determine which social agents are involved in the political debate on Twitter and whether the interpretive hegemony of actors that have traditionally been the most prominent is tempered by the challenge of framing shared with audiences. The relationship between the interpretations expressed and the profiles of participants is analyzed in comparison with the frames used by mainstream media. The chosen methodology combines content analysis and discourse analysis techniques on a sample of 1,504 relevant tweets posted on two political issues –the approval of the education law LOMCE and the evictions caused by the crisis, which have also been studied in the front pages of four leading newspapers in Spain. The results show a correlation between political issue singularities, frames and the type of discussion depending on the participants.