Biodegradation of 2,4,6-trichlorophenol in the presence of primary substrate by immobilized pure culture bacteria

In this study, pure strains that are capable of utilizing 2,4,6-trichlorophenol have been isolated from the mixed culture grown on substrates containing chlorophenolic compounds. Studies have been carried out on the capability of these isolated pure strains in suspended and immobilized forms to decompose 2,4,6-trichlorophenol. Additionally, the influence of primary substrates (e.g., phenol, 2-chlorophenol, 3-chlorophenol, 4-chlorophenol, 2,4-dichlorophenol) on the decomposition of 2,4,6-trichlorophenol by the isolated pure strains grown in immobilized form is also investigated. The results are: Through bacterial isolation and identification, three pure strains have been obtained: Pseudomonas spp. strain 01, Pseudomonas spp. strain 02 and Agrobacterium spp. Whether in suspended or immobilized forms, all strains have poor removal efficiencies of 2,4,6-trichlorophenol. However, addition of 200 mg/l phenol will enable the immobilized Pseudomonas spp. strain 01, and Pseudomonas spp. strain 02 to achieve 65% and 48% removal of 2,4,6-trichlorophenol, respectively. Addition of phenol will assist the immobilized Pseudomonas spp. strain 02 in achieving removal of 2,4,6-trichlorophenol but the removal efficiency is not good if the phenol concentration is too low. The optimum phenol concentration should be between 200 and 400 mg/l.     

Solar photocatalytic mineralization of commercial pesticides: acrinathrin

A comparative study of the degradation of commercial acrinathrin spiked in water using TiO2 photocatalysis and photolysis under sunlight was performed. Samples were analysed by liquid chromatography-diode array detector (HPLC-DAD) and gas chromatography-ion trap-mass spectrometric detector (GC-ITMS). Additional total organic carbon (TOC) analyses were carried out to evaluate the mineralisation rates. One photoproduct, 2-phenoxy benzaldehyde, was unequivocally identified and evaluated by GC-ITMS during the processes. Although acrinathrin is almost destroyed when exposed to irradiation for more than 400 h, photocatalysis with TiO2 noticeably reduced degradation to a few hours. In this case, with the additional presence of peroxydisulphate, in less than 2 h acrinathrin is completely destroyed. Mineralisation of acrinathrin, without catalyst, was only around 50% after 400 h of irradiation.     

Semiconductor-assisted photocatalytic degradation of reactive dyes in aqueous solution

This work reports the semiconductor-assisted photochemical degradation of reactive dyes. In an oxygenated-UV-ZnO system almost total decolorization of Remazol Brilliant Blue R, Remazol Black B, Reactive Blue 221 and Reactive Blue 222 was observed in reaction times of about 60 min. Extending the photochemical treatment up to 120 min, mineralization higher than 80% for all the dyes was observed. During the same period, the residual acute toxicity was significantly reduced only for Remazol Black B. A systematic optimization study carried out by factorial design showed that for the reactive dyes tested, the ZnO semiconductor exhibits a better efficiency than that observed with anatase TiO2. A synergistic effect in the coupled TiO2-ZnO system was not observed.     

Forecasts using neural network versus Box-Jenkins methodology for ambient air quality monitoring data

This study explores ambient air quality forecasts using the conventional time-series approach and a neural network. Sulfur dioxide and ozone monitoring data collected from two background stations and an industrial station are used. Various learning methods and varied numbers of hidden layer processing units of the neural network model are tested. Results obtained from the time-series and neural network models are discussed and compared on the basis of their performance for 1-step-ahead and 24-step-ahead forecasts. Although both models perform well for 1-step-ahead prediction, some neural network results reveal a slightly better forecast without manually adjusting model parameters, according to the results. For a 24-step-ahead forecast, most neural network results are as good as or superior to those of the time-series model. With the advantages of self-learning, self-adaptation, and parallel processing, the neural network approach is a promising technique for developing an automated short-term ambient air quality forecast system.     

Interpreting the relationship between pheromone component emission from commercial lures and captures of Helicoverpa zea (Boddie) in bucket and cone traps

Male corn earworm moths, Helicoverpa zea (Boddie), were captured in conical Texas pheromone traps (cone traps) and bucket traps baited with four different commercial lures manufactured by three different manufacturers. Because significant numbers were captured in bucket traps baited with some of the lures, and none with others, the volatile emissions from all of the lures were sampled and analyzed by gas chromatographic methods. The numbers of males captured in two types of trap were compared with bait emissions in an endeavor to define a more effective lure for bucket traps. The lure from one manufacturer captured the same numbers of males in both trap types; one captured more in bucket traps than in cone traps, and another captured only a small number in bucket traps. The emission rate of all active compounds from each of the different lures was approximately linear for the duration of the assays. A gas-liquid chromatographic peak associated with a third compound, (Z)-9-tetradecenal, which reduces behavioral responses, was observed in the emissions from all lures evaluated. The effectiveness of the Hercon (Emmigsville, PA) lure in capturing males in both types of trap was associated with a lower emission of (Z)-11-hexadecenal, (Z)-9-hexadecenal and (Z)-9-tetradecenal than from the other lures.     

Innovations strategy for moving from created regional clusters to co-creation in life sciences for health care and well-being ecosystems

Environmental Science and Pollution Research - Over the last decades, the demographic changes have all altered the population structure and influenced the social, economic, and political...     

Steel mill waste application in soil: dynamics of potentially toxic elements in rice and health risk perspectives

Environmental Science and Pollution Research - Potentially toxic elements (PTEs) are of great concern in steel mill wastes. Therefore, in order to use them as potential fertilizers in soil, risk...     

The Cramer’s rule for the parametrization of phenol and its hydroxylated byproducts: UV spectroscopy vs. high performance liquid chromatography

Environmental Science and Pollution Research - A linear algebra theorem like Cramer’s rule was used for the analysis of a system of equations obtained from UV spectroscopy, and results were...     

Anti-kindling effect of Ginkgo biloba leaf extract and L-carnitine in the pentylenetetrazol model of epilepsy

Environmental Science and Pollution Research - Epilepsy is one of the most common serious brain disorders, affecting about 1% of the population all over the world. Ginkgo biloba extract (GbE) and...     

Heavy metal pollution and forest health in the Ukrainian Carpathians

The Ukrainian Carpathians are characterized by high air pollution caused by emissions from numerous industries. We have been monitoring the state of forests in this region since 1989. The highest levels of tree defoliation (>30%) are found close to industrial emission sources and in the upper mountain forests of the Ivano-Frankivsk and Chernivtsi regions. This is caused by a combination of strong anthropogenic influences (pollution, illegal uses, recreation) as well as poor site and climatic conditions. In the Ivano-Frankivsk region, Cd and Mo accumulate in forest soils; Cr, Mo and Zn soil concentrations are higher than their limit levels; and Pb concentrations exceed toxic levels close to industrial areas (10% of the region territory). Local background levels of heavy metals are greatly exceeded in snow close to industrial regions. Analysis of correlation matrices shows that the chemical elements Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, V and Zn occur at pollution levels in natural ecosystems in the Ukrainian Carpathians. Maximum concentrations of toxic elements occur in the oak forest zone; the most industrially developed area of the region. Toxic heavy metals in the Ukrainian Carpathians forests enter with precipitation and dustfall, then become fixed in soil and accumulate in leaves, needles of vascular plants and mosses. Concentrations of these metals decrease with altitude: highest in the oak forests, less in beech, and lowest in the spruce forest zones. However, some chemical elements have the highest concentrations in spruce forests; V in needles, As in snow, and Ba and Al in soils.