Enzyme-Retted Flax Fiber and Recycled Polyethylene Composites

Municipal solid wastes generated each year contain potentially useful and recyclable materials for composites. Simultaneously, interest is high for the use of natural fibers, such as flax (Linum usitatissimum L.), in composites thus providing cost and environmental benefits. To investigate the utility of these materials, composites containing flax fibers with recycled high density polyethylene (HDPE) were created and compared with similar products made with wood pulp, glass, and carbon fibers. Flax was either enzyme- or dew-retted to observe composite property differences between diverse levels of enzyme formulations and retting techniques. Coupling agents would strengthen binding between fibers and HDPE but in this study fibers were not modified in anyway to observe mechanical property differences between natural fiber composites. Composites with flax fibers from various retting methods, i.e., dew- vs. enzyme-retting, behaved differently; dew-retted fiber composites resulted in both lower strength and percent elongation. The lowest level of enzyme-retting and the most economical process produces composites that do not appear to differ from the highest level of enzyme-retting. Flax fibers improved the modulus of elasticity over wood pulp and HDPE alone and were less dense than glass or carbon fiber composites. Likely, differences in surface properties of the various flax fibers, while poorly defined and requiring further research, caused various interactions with the resin that influenced composite properties.     

Cultural and individual differences in self‐rating behavior: an extension and refinement of the cultural relativity hypothesis

This study examined the relationships between culture, individual attributes, and self‐rating behavior among 1,786 university students in Canada, Hong Kong, Taiwan, mainland China, and Japan, and in doing so extended and refined the cultural relativity hypothesis. It explored the difference between vertical and horizontal individualists in self‐rating behavior, and examined the mediating effects of two individual attributes, self‐enhancement propensity and general self‐efficacy in the relationship between individualism and self‐rating behavior. The results confirmed that individualism is the cultural driver for self‐rating leniency, and that the individual‐level assessment of individualism is a stronger predictor of self‐rating leniency than are culture‐level differences. Vertical individualism was found to be positively related to self‐enhancement propensity, which in turn was positively related to self‐rating. Whereas, horizontal individualism was positively related to general self‐efficacy, which in turn had a positive relationship with self‐rating. We discuss the implications of the results for academic research and practical management. Copyright © 2006 John Wiley & Sons, Ltd.     

Explosions of carbon black and propane hybrid mixtures

Explosions of hybrid mixtures, i.e. mixtures containing more than one combustible phase, are not well understood. Most studies in this area involve mixtures of common dusts and gases, such as coal and methane, or polyethylene and ethylene. The present work focuses on explosions of carbon black particles, i.e. almost pure carbon with a very low content of volatiles: this makes the process of explosion less intense. However, addition of some quantities of combustible gases (here: propane) may sustain combustion processes. Another important issue is the fact that the carbon black particles are smaller in size than most dusts encountered in the process industry. The experiments were carried out in a 20-L explosion vessel and the analysis of the results focuses on the maximum explosion pressures and the maximum rates of pressure rise as a function of carbon black and propane concentrations. In addition, some samples of unburnt dust were collected and analysed with a scanning electron microscope and with thermo-gravimetric analysis.     

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models

Source apportionment study of PM₁₀ (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM₁₀.     

Photodegradation of Oryzalin in aqueous isopropanol and acetonitrile

The phototransformation of Oryzalin was studied under UV light (λ_max ≥ 290 nm) and sunlight (λ_max ≥ 250 nm) in aqueous isopropanol and acetonitrile solution in absence and presence of TiO₂ as sensitizer. The rate of photodegradation of Oryzalin in different solvent system followed first-order kinetics, and calculated half-lives were found to be in the range of 23.52-53.75 h for UV light and 41.23-61.43 h for sunlight. From this study, total 12 photoproducts were identified and characterized on the basis of column chromatography and Q-Tof micromass spectral data. The plausible mechanism of phototransformation involved was hydrolysis, breaking of sulfonic bond, and loss of amino and sulfonic acid group.     

Airborne pollutants along a roadside: assessment using snow analyses and moss bags

Vertical snow sampling and moss bag transplants were used to estimate the local inorganic and organic pollutant load deposited from traffic along a major highway in Finland. The pH and concentrations of Cl(-), NO(3)(-), SO(4)(2-), Ca(2+), Na(+) and polyaromatic hydrocarbons (PAHs) were determined from snow samples collected in winter at different sites along the highway. In summer, moss bags containing 20 g of fresh red-stemmed feather moss (Pleurozium schreberi) were transplanted at the same sites. The moss bag transplants remained exposed to roadside traffic for a period of one month following which the samples were collected and the PAH profiles and concentrations were analysed. The deposition of inorganic and organic pollutants from road traffic was observed up to 60 m from the road. The prevailing winds had a significant effect on the dispersion of pollutants. Snow appears to be a good collector of inorganic pollutants from the atmosphere and can be used to monitor local airborne pollution from road traffic. Snow packs can also be used as passive collectors of organic pollutant loads from road traffic on a local scale. To monitor organic PAH deposition from the road traffic, moss bags appeared to be better indicators compared to snow sampling. The efficiency of moss bags in accumulating PAH compounds indicate that vegetation may be an important sink for traffic pollution.     

Regression modelling of hourly NOx and NO2 concentrations in urban air in London

Based on hourly measurements of NO_x NO₂ and O₃ and meteorological data, an ordinary least squares (OLS) model and a first-order autocorrelation (AR) model were developed to analyse the regression and prediction of NO_x and NO₂ concentrations in London. Primary emissions and wind speed are the most important factors influencing NO_x concentrations; in addition to these two, reaction of NO with O₃ is also a major factor influencing NO₂ concentrations. The AR model resulted in high correlation coefficients (R > 0.95) for the NO_x and NO₂ regression based on a whole year's data, and is capable of predicting NO₂ (R = 0.83) and NO_x (R = 0.65) concentrations when the explanatory variables were available. The analysis of the structure of regression models by Principal Component Analysis (PCA) indicates that the regression models are stable. The results of the OLS model indicate that there was an exceptional NO₂ source, other than primary emission and reaction of NO with O₃, in the air pollution episode in London in December 1991.