In this paper the two effluents from PBA (3- phenoxy -benzaldehyde) productionprocess were treated by polymeric adsorbent CHA-lll. PBA or PBC(3-phenoxybenzoic acid) was recovered from the wastewater in the process of ...
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In this paper the two effluents from PBA (3- phenoxy -benzaldehyde) productionprocess were treated by polymeric adsorbent CHA-lll. PBA or PBC(3-phenoxybenzoic acid) was recovered from the wastewater in the process of neutralization. As asecondary treatment method, adsorption with CHA-lll showed better efficency thanPhotocatalytic decomposition and solvent extraction. The optimal technologicalparameters were: adsorption: current velocity: 2.0 BV/hr(bed volume per hour), roomtemperature, desorption: current velocity:10 BV/hr 80℃8% sodium hydroxideaqueous solutions. In conclusion, 90.9% COD in the neutralizing wastewater and98. 4% COD in the hydrolysis wastewater are removed successfully.
The sorption behavior of 15 substituted benzaldehydes on natural soil has been reported. It was found that most of the sorption isotherms were nonlinear, log Kf correlated poorly with log Kow and log Sw. Descriptors d...
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The sorption behavior of 15 substituted benzaldehydes on natural soil has been reported. It was found that most of the sorption isotherms were nonlinear, log Kf correlated poorly with log Kow and log Sw. Descriptors derived from quantum computation were used to develop a QSPR model, which could be used to predict the log Kf of similar compounds. This study snowed that the gap (ΔE) between the energy of the lowest unoccupied molecular orbital and the energy of the highest occupied molecular orbital was the principle factor controlling the sorption behavior of tested chemicals. Other important variables contained the most positive net atomic charge on an atom (q+ ) and final heat of formation (HF). This shows that chemosorption and physical adsorption may be the fundamental process for benzaldehydes sorption on natural soil other than lipophilic partitioning.
Chlorinated disinfection byproducts (DBPs) are formed by chlorination of drinking water. In this study, laboratory chlorination experiments were conducted with respect to the influence of reaction time, TOC, chlorine ...
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Chlorinated disinfection byproducts (DBPs) are formed by chlorination of drinking water. In this study, laboratory chlorination experiments were conducted with respect to the influence of reaction time, TOC, chlorine dose, pH and temperature on formation of POX (purgeable organic halide) and NPOX (non-purgeable organic halide). Non-linear regression models were generated as follows: [POX] = 7.2t(0.08)[TOC](0.49)[Cl-2](0.41)(pH + 8.6) e((-468 5/T)) [NPOX] = 28.7t(0/07)[TOC](0.53)[Cl-2](0.44)(20.9 - pH) e((-632 4/T)) where t is the reaction time (h), [TOC] is the concentration of total organic carbon (md/l), [Cl-2] is the concentration of applied chlorine dose (mg/l) and T is the absolute temperature (K). Further, the above models were tested with three water samples. We have also investigated the influence of coexistent ammonia-nitrogen. (C) 1997 Elsevier Science Ltd.
The article cites a study that investigates the bioconcentration process of copper, cadmium and the influence of organic chelation compounds like ethylenediamine tetraacetic acid at environmentally elevated concentrat...
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The article cites a study that investigates the bioconcentration process of copper, cadmium and the influence of organic chelation compounds like ethylenediamine tetraacetic acid at environmentally elevated concentrations at various times of exposure of carps. The diffusion process of metals in the skin and gills of fish is the main pathway for the bioconcentration of metal ions indicating that the molecular size, stability of complexes and ion charges can modify the bioconcentration process of heavy metals. It was exhibited that metals have low abilities to diffuse in the skin and gills of fishes. The consumption of heavy metals even with organic chelation compounds was less due to the formation of stable metal-chelate complexes that are poorly absorbed during the diffusion of the fish.
Based on MTLSER model and quantum chemical descriptors computed by the AM1 hamiltonian, two Quantitative Structure-Activity Relationship (QSAR) equations for 28 alkyl (1-phenylsulfonyl) cycloalkane-carboxylates were o...
Based on MTLSER model and quantum chemical descriptors computed by the AM1 hamiltonian, two Quantitative Structure-Activity Relationship (QSAR) equations for 28 alkyl (1-phenylsulfonyl) cycloalkane-carboxylates were obtained. Polarizability is the most significant term influencing toxicity. The toxicity increased with the increase of polarizability and the most negative net atomic charges on oxygen atoms in the sulfone group of the compounds and decreased with the increase of dipole moment and the most positive net atomic charges on a hydrogen atom of the compounds. This study proved the advantages of the MTLSER model (a) The quantum chemical descriptors in the model can be easily and precisely obtained by computation instead of experiment, a large amount of expenses and time can be saved;(b) The quantum chemical descriptors have clear physicochemical interpretations, and interpretation of the correlation equations can suggest modes of interaction between toxicants and organisms;(c) The MTLSER mode can be used for compounds for which the solvatochromic parameters are not available. (C) 1997 Elsevier Science Ltd.
In the present study, pseudo-first-order direct photolysis rate constants of 17 PAHs were determined. Basing on the frontier molecular energy, E(homo) and E(lumo), a QSPR equation was obtained. The obtained equation c...
In the present study, pseudo-first-order direct photolysis rate constants of 17 PAHs were determined. Basing on the frontier molecular energy, E(homo) and E(lumo), a QSPR equation was obtained. The obtained equation can be used to predict photolysis rate constants of PAHs under the irradation of medium pressure mercury lamp. As shown in the following equation, the obtained relationship between the logarithm of photolysis rate constants(logk(exp)) and E(lumo)-E(homo) gap was parabolic. logk(exp)=-32.738+9.770(E(lumo)-E(homo))-0.715(E(lumo)-E(homo))(2) n=17, r=0.921, SE=0.322, F=38.911, p=0.0000 Where r is the multiple correlation coefficient, SE is the standard error of estimates for the full regression, F is the F value for analysis of variance, p is the significance level. The obtained parabolic relationship is reasonable when internal and external factors controlling photolysis rate are considered. Copyright (C) 1996 Elsevier Science Ltd.
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