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.     

An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

The deep-sea as a final global sink of semivolatile persistent organic pollutants? Part I: PCBs in surface and deep-sea dwelling fish of the north and south Atlantic and the Monterey Bay Canyon (California)

The understanding of the global environmental multiphase distribution of persistent organic pollutants (POPs) as a result of the physico-chemical properties of the respective compounds is well established. We have analysed the results of a vertical transport of POPs from upper water layers (0-200 m) to the deepwater region (> 800 m) in terms of the contamination of the biophase in both water layers. The contents of persistent organochlorine compounds like polychlorinated biphenyls (PCBs) in fish living in the upper water layers of the North Atlantic and the South Atlantic, and at the continental shelf of California (Marine Sanctuary Monterey Bay and its deep-sea Canyon) are compared to the levels in deep-sea or bottom dwelling fish within the same geographic area. The deep-sea biota show significantly higher burdens as compared to surface-living species of the same region. There are also indications for recycling processes of POPs--in this case the PCBs--in the biophase of the abyss as well. It can be concluded that the bio- and geo phase of the deep-sea may act similarly as the upper horizons of forest and grasslands on the continents as an ultimate global sink for POPs in the marine environment.     

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.     

Inflammation biomarkers associated with arsenic exposure by drinking water and respiratory outcomes in indigenous children from three Yaqui villages in southern Sonora,México

Environmental Science and Pollution Research - Environmental arsenic exposure in adults and children has been associated with a reduction in the expression of club cell secretory protein (CC16) and...     

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...     

Glyphosate concentrations in global freshwaters: are aquatic organisms at risk?

Environmental Science and Pollution Research - Glyphosate is the most used herbicide worldwide. Many studies have reported glyphosate risks to aquatic organisms of different trophic levels....     

Hg concentrations and stable isotope variations in tropical fish species of a gold-mining-impacted watershed in French Guiana

Environmental Science and Pollution Research - The aim of the study was to determine if gold-mining activities could impact the mercury (Hg) concentrations and isotopic signatures in freshwater...