956 resultados para Hazardous materials response
Resumo:
HDTMA+ pillared montmorillonites were obtained by pillaring different amounts of the surfactant hexadecyltrimethylammonium bromide (HDTMAB) into sodium montmorillonite (Na-Mt) in an aqueous solution. The optimum conditions and batch kinetics of sorption of p-nitrophenol from aqueous solutions were reported. The solu-tion pH had a very important effect on the sorption of p-nitrophenol. The maximum p-nitrophenol absorption/adsorption occurs when solution pH (7.15~7.35) is approx-imately equal to the pKa (7.16) of the p-nitrophenol ion deprotonation reaction. X-ray diffraction analysis showed that surfactant cations had been pillared into the interlayer and the p-nitrophenol affected the arrangement of surfactant. With the increased con-centration of surfactant cations, the arrangement of HDTMA+ within the clay inter-layer changes and the sorption of p-nitrophenol increases. HDTMA+ pillared mont-morillonites are more effective than Na-Mt for the adsorption of p-nitrophenol from aqueous solutions. The Langmuir, Freundlich and dual-mode sorption were tested to fit the sorption isotherms.
Resumo:
Traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) pose a serious threat to human and ecosystem health when washed off into receiving water bodies by stormwater. Climate change influenced rainfall characteristics makes the estimation of these pollutants in stormwater quite complex. The research study discussed in the paper developed a prediction framework for such pollutants under the dynamic influence of climate change on rainfall characteristics. It was established through principal component analysis (PCA) that the intensity and durations of low to moderate rain events induced by climate change mainly affect the wash-off of SVOCs and NVOCs from urban roads. The study outcomes were able to overcome the limitations of stringent laboratory preparation of calibration matrices by extracting uncorrelated underlying factors in the data matrices through systematic application of PCA and factor analysis (FA). Based on the initial findings from PCA and FA, the framework incorporated orthogonal rotatable central composite experimental design to set up calibration matrices and partial least square regression to identify significant variables in predicting the target SVOCs and NVOCs in four particulate fractions ranging from >300-1 μm and one dissolved fraction of <1 μm. For the particulate fractions range >300-1 μm, similar distributions of predicted and observed concentrations of the target compounds from minimum to 75th percentile were achieved. The inter-event coefficient of variations for particulate fractions of >300-1 μm were 5% to 25%. The limited solubility of the target compounds in stormwater restricted the predictive capacity of the proposed method for the dissolved fraction of <1 μm.
Resumo:
Phenols are well known noxious compounds, which are often found in various water sources. A novel analytical method has been researched and developed based on the properties of hemin–graphene hybrid nanosheets (H–GNs). These nanosheets were synthesized using a wet-chemical method, and they have peroxidase-like activity. Also, in the presence of H2O2, the nanosheets are efficient catalysts for the oxidation of the substrate, 4-aminoantipine (4-AP), and the phenols. The products of such an oxidation reaction are the colored quinone-imines (benzodiazepines). Importantly, these products enabled the differentiation of the three common phenols – pyrocatechol, resorcin and hydroquinone, with the use of a novel, spectroscopic method, which was developed for the simultaneous determination of the above three analytes. This spectroscopic method produced linear calibrations for the pyrocatechol (0.4–4.0 mg L−1), resorcin (0.2–2.0 mg L−1) and hydroquinone (0.8–8.0 mg L−1) analytes. In addition, kinetic and spectral data, obtained from the formation of the colored benzodiazepines, were used to establish multi-variate calibrations for the prediction of the three phenol analytes found in various kinds of water; partial least squares (PLS), principal component regression (PCR) and artificial neural network (ANN) models were used and the PLS model performed best.
Resumo:
Managing sludge generated by treating groundwater contaminated with geogenic contaminants (fluoride, arsenic, and iron) is a major issue in developing nations. Their re-use in civil engineering applications is a possible pathway for reducing the impact on the geo-environment. This paper examines the re-use of one such sludge material, namely, fluoride contaminated bone char sludge, as partial replacement for fine aggregate (river-sand) in the manufacture of dense concrete specimens. Bone char sludge is being produced by defluoridation of contaminated groundwater in Nalagonda District, Andhra Pradesh, India. The impact of admixing 1.5-9% sludge contents on the compression strength and fluoride leaching potential of the sludge admixed concrete (SAC) specimens are examined. The compression strengths of the SAC specimensa re examined with respect to strength criteria for manufacture of dense, load-bearing concrete blocks. The fluoride release potential of the SAC specimens is examined with respect to standards specific to disposal of treated leachate into inland surface water.
Resumo:
Heavy metals build-up on urban road surfaces is a complex process and influenced by a diverse range of factors. Although numerous research studies have been conducted in the area of heavy metals build-up, limited research has been undertaken to rank these factors in terms of their influence on the build-up process. This results in limitations in the identification of the most critical factor/s for accurately estimating heavy metal loads and for designing effective stormwater treatment measures. The research study undertook an in-depth analysis of the factors which influence heavy metals build-up based on data generated from a number of different geographical locations around the world. Traffic volume was found to be the highest ranked factor in terms of influencing heavy metals build-up while land use was ranked the second. Proximity to arterial roads, antecedent dry days and road surface roughness has a relatively lower ranking. Furthermore, the study outcomes advances the conceptual understanding of heavy metals build-up based on the finding that with increasing traffic volume, total heavy metal build-up load increases while the variability decreases. The outcomes from this research study are expected to contribute to more accurate estimation of heavy metals build-up loads leading to more effective stormwater treatment design.
Resumo:
Batch adsorption of fluoride onto manganese dioxide-coated activated alumina (MCAA) has been studied. Adsorption experiments were carried out at various pH (3–9), time interval (0–6 h), adsorbent dose (1–16 g/l), initial fluoride concentration (1–25 mg/l) and in the presence of different anions. Adsorption isotherms have been modeled using Freundlich, Langmuir and Dubinin–Raduskevich isotherms and adsorption followed Langmuir isotherm model. Kinetic studies revealed that the adsorption followed second-order rate kinetics. MCAA could remove fluoride effectively (up to 0.2 mg/l) at pH 7 in 3 h with 8 g/l adsorbent dose when 10 mg/l of fluoride was present in 50 ml of water. In the presence of other anions, the adsorption of fluoride was retared. The mechanism of fluoride uptake by MCAA is due to physical adsorption as well as through intraparticle diffusion which was confirmed by kinetics, Dubinin–Raduskevich isotherm, zeta-potential measurements and mapping studies of energy-dispersive analysis of X-ray.
Resumo:
The photocatalytic degradation of five anionic, eight cationic and three solvent dyes using combustion-synthesized nano-TiO2 (CSTiO2) and commercial Degussa P-25 TiO2 (DP-25) were evaluated to determine the effect of the functional group in the dye. The degradation of the dyes was quantified using the initial rate of decolorization and mineralization. The decolorization of the anionic dyes with CSTiO2 followed the order: indigo carmine > eosin Y > amido black 10B > alizarin cyanine green > orange G. The decolorization of the cationic dyes with DP-25 followed the order: malachite green > pyronin Y > rhodamine 6G > azure B > nile blue sulfate > auramine O approximate to acriflavine P approximate to safranin O. CSTiO2 showed higher rates of decolorization and mineralization for all the anionic dyes compared to DP-25, while DP-25 was better in terms of decolorization for most of the cationic dyes. The solvent dyes exhibited adsorption dependent decolorization. The order of decolorization and mineralization of the anionic and cationic dyes (a) with CS TiO2 and DP-25 was different and correlated with the surface properties of these catalysts (b) were rationalized with the molecular structure of the dye and the degradation pathway of the dye. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
The hazards associated with major accident hazard (MAN) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identification and quantification of these hazards related to chemical industries. Fault tree analysis (FTA) is an established technique in hazard identification. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. This paper outlines the estimation of the probability of release of chlorine from storage and filling facility of chlor-alkali industry using FTA. An attempt has also been made to arrive at the probability of chlorine release using expert elicitation and proven fuzzy logic technique for Indian conditions. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two-dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor involved in expert elicitation. (C) 2010 Elsevier B.V. All rights reserved.