Decomposition of toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008

This study analyzes toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008. Decomposition analysis applying the logarithmic mean Divisia index is used to analyze changes in toxic chemical substance emissions by the following five factors: cleaner production, end-of-pipe treatment, transfer for further management, mixing of intermediate materials, and production scale. Based on our results, the chemical manufacturing sector reduced toxic chemical substance emissions mainly via end-of-pipe treatment. In the meantime, transfer for further management contributed to the reduction of toxic chemical substance emissions in the metal fabrication industry. This occurred because the environmental business market expanded in the 1990s, and the infrastructure for the recycling of metal and other wastes became more efficient. Cleaner production is the main contributor to toxic chemical reduction in the electrical product industry. This implies that the electrical product industry is successful in developing a more environmentally friendly product design and production process.

Decomposition of the environmental Kuznets curve : scale, technique, and composition effects

This study decomposed the determinants of environmental quality into scale, technique, and composition effects. We applied a semiparametric method of generalized additive models, which enabled us to use flexible functional forms and include several independent variables in the model. The differences in the technique effect were found to play a crucial role in reducing pollution. We found that the technique effect was sufficient to reduce sulfur dioxide emissions. On the other hand, its effect was not enough to reduce carbon dioxide (CO2) emissions and energy use, except for the case of CO2 emissions in high-income countries.

Insight into the thermal decomposition of kaolinite intercalated with potassium acetate : an evolved gas analysis

The thermal decomposition process of kaolinite–potassium acetate intercalation complex has been studied using simultaneous thermogravimetry coupled with Fourier-transform infrared spectroscopy and mass spectrometry (TG-FTIR-MS). The results showed that the thermal decomposition of the complex took place in four temperature ranges, namely 50–100, 260–320, 320–550, and 650–780 °C. The maximal mass losses rate for the thermal decomposition of the kaolinite–potassium acetate intercalation complex was observed at 81, 296, 378, 411, 486, and 733 °C, which was attributed to (a) loss of the adsorbed water, (b) thermal decomposition of surface-adsorbed potassium acetate (KAc), (c) the loss of the water coordinated to potassium acetate in the intercalated kaolinite, (d) the thermal decomposition of intercalated KAc in the interlayer of kaolinite and the removal of inner surface hydroxyls, (e) the loss of the inner hydroxyls, and (f) the thermal decomposition of carbonate derived from the decomposition of KAc. The thermal decomposition of intercalated potassium acetate started in the range 320–550 °C accompanied by the release of water, acetone, carbon dioxide, and acetic acid. The identification of pyrolysis fragment ions provided insight into the thermal decomposition mechanism. The results showed that the main decomposition fragment ions of the kaolinite–KAc intercalation complex were water, acetone, carbon dioxide, and acetic acid. TG-FTIR-MS was demonstrated to be a powerful tool for the investigation of kaolinite intercalation complexes. It delivers a detailed insight into the thermal decomposition processes of the kaolinite intercalation complexes characterized by mass loss and the evolved gases.

Turbulence measurements in a shallow tidal estuary : analysis based on triple decomposition

In an estuary, mixing and dispersion are the result of the combination of large scale advection and small scale turbulence which are both complex to estimate. A field study was conducted in a small sub-tropical estuary in which high frequency (50 Hz) turbulent data were recorded continuously for about 48 hours. A triple decomposition technique was introduced to isolate the contributions of tides, resonance and turbulence in the flow field. A striking feature of the data set was the slow fluctuations which exhibited large amplitudes up to 50% the tidal amplitude under neap tide conditions. The triple decomposition technique allowed a characterisation of broader temporal scales of high frequency fluctuation data sampled during a number of full tidal cycles.

Analysing the similarity of proteins based on a new approach to empirical mode decomposition

The function of a protein can be partially determined by the information contained in its amino acid sequence. It can be assumed that proteins with similar amino acid sequences normally have closer functions. Hence analysing the similarity of proteins has become one of the most important areas of protein study. In this work, a layered comparison method is used to analyze the similarity of proteins. It is based on the empirical mode decomposition (EMD) method, and protein sequences are characterized by the intrinsic mode functions (IMFs). The similarity of proteins is studied with a new cross-correlation formula. It seems that the EMD method can be used to detect the functional relationship of two proteins. This kind of similarity method is a complement of traditional sequence similarity approaches which focus on the alignment of amino acids

Acoustic feature extraction using perceptual wavelet packet decomposition for frog call classification

Frog protection has become increasingly essential due to the rapid decline of its biodiversity. Therefore, it is valuable to develop new methods for studying this biodiversity. In this paper, a novel feature extraction method is proposed based on perceptual wavelet packet decomposition for classifying frog calls in noisy environments. Pre-processing and syllable segmentation are first applied to the frog call. Then, a spectral peak track is extracted from each syllable if possible. Track duration, dominant frequency and oscillation rate are directly extracted from the track. With k-means clustering algorithm, the calculated dominant frequency of all frog species is clustered into k parts, which produce a frequency scale for wavelet packet decomposition. Based on the adaptive frequency scale, wavelet packet decomposition is applied to the frog calls. Using the wavelet packet decomposition coefficients, a new feature set named perceptual wavelet packet decomposition sub-band cepstral coefficients is extracted. Finally, a k-nearest neighbour (k-NN) classifier is used for the classification. The experiment results show that the proposed features can achieve an average classification accuracy of 97.45% which outperforms syllable features (86.87%) and Mel-frequency cepstral coefficients (MFCCs) feature (90.80%).

Modeling of sonochemical decomposition of CCI4 in aqueous solutions

In the context of removal of organic pollutants from wastewater, sonolysis of CCl4 dissolved in water has been widely investigated. These investigations are either completely experimental or correlate data empirically. In this work, a quantitative model is developed to predict the rate of sonolysis of aqueous CCl4. The model considers the isothermal growth and partially adiabatic collapse of cavitation bubbles containing gas and vapor leading to conditions of high temperatures and pressures in them, attainment of thermodynamic equilibrium at the end of collapse, release of bubble contents into the liquid pool, and reactions in the well-mixed pool. The model successfully predicts the extent of degradation of dissolved CCl4, and the influence of various parameters such as initial concentration of CCl4, temperature, and nature of gas atmosphere above the liquid. in particular, it predicts the results of Hua and Hoffmann (Environ. Sci Technol, 1996, 30, 864-871), who found that degradation is first order with CCl4 and that Argon as well as Ar-O-3 atmospheres give the same results. The framework of the model is capable of quantitatively describing the degradation of many dissolved organics by considering all the involved species.

Synthesis, structure and spectroscopic studies on hydroxo-bridged heterotrinuclear complexes of cobalt(m) with ethane-l,2-diamine and ammonia as terminal ligands

Hydroxo-bridged homo- and hetero-trinuclear cobalt(III) complexes of the type [MII(H2O)2{(OH)2CoIII(N4)}2]X2·nH2O [MII= a divalent metal ion such as CoII, NiII or ZnII; N4=(en)2(en = ethane-1,2-diamine) or (NH3)4; X = SO4 or (ClO4)2; n= 3 or 5] have been prepared and spectroscopically characterized. The structure of [Cu{(OH)2Co(en)2}2][SO4]2·2H2O 1 has been determined. The geometry around copper atom is a pseudo-square-based pyramid, with the basal sites occupied by four bridging hydroxide oxygens and the apical site is occupied by a weakly co-ordinated sulfate anion [Cu–O 2.516(4)Å]. The hydroxo groups bridge pairs of cobalt(III) ions which are in near-octahedral environments. The ethylenediamine chelate rings have the twist conformation. In the crystal structure of [Cu{(OH)2Co(en)2}2][ClO4]4·2H2O 2 the perchlorate ion is not co-ordinated and the en ligands have envelope conformations. The sulfate ion in [Cu{(OH)2Co(NH3)4}2][SO4]2·4H2O 3 is not co-ordinated to the central copper ion. Electronic, infrared and variable-temperature EPR spectral data are discussed.

Steady state optimization of an ammonia reactor

A hybrid simulation technique for identification and steady state optimization of a tubular reactor used in ammonia synthesis is presented. The parameter identification program finds the catalyst activity factor and certain heat transfer coefficients that minimize the sum of squares of deviation from simulated and actual temperature measurements obtained from an operating plant. The optimization program finds the values of three flows to the reactor to maximize the ammonia yield using the estimated parameter values. Powell's direct method of optimization is used in both cases. The results obtained here are compared with the plant data.

Studies in metal-ammonia reduction-5: Reduction and reductive methylation of some naphthoic acids

Birch reductio and reductive methylations of some substituted naphtholic acids have been examined. The factors influencing the mechanism of reduction process have been discussed. Some of the reduced naphthoic acids are useful synthons for synthesis.

Effect of Prior Ultraviolet Irradiation on Thermal Decomposition and Ignition of Coal

Prior ultraviolet irradiation of coal results in catalysing the subsequent thermal decomposition and ignition of coal. Mechanically, it is shown that ultraviolet radiation brings about the catalysis by acting on the inorganic components of coal.

State space formulation of ammonia reactor dynamics

The specific objective of this paper is to develop a state space model of a tubular ammonia reactor which is the heart of an ammonia plant in a fertiliser complex. A ninth order model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. The lumped model is chosen such that the steady state temperature at the exit of the catalyst bed computed from the simplified state space model is close enough to the one computed from the nonlinear steady state model. The model developed in this paper is very useful for the design of continuous/discrete versions of single variable/multivariable control algorithms.

Kinetics of thermal decomposition of strontium zirconyl carbonate, Sr2Zr2O5CO3

The kinetics of decomposition of the carbonate Sr2Zr2O5CO3, are greatly influenced by the thermal effects during its formation. (α−t) curves are found to be sigmoidal and they could be analysed based on power law equations followed by first-order decay. The presence of carbon in the vacuum-prepared sample of carbonate has a strong deactivating effect. The carbonate is fairly crystalline and its decomposition leads to the formation of crystalline strontium zirconate.