Non-aqueous dispersions of particles and their applications

In the current work, three studies about non-aqueous dispersions of particles were carried out by using an amphiphilic block copolymer poly(isoprene)-block-poly(methyl methacrylate) (PI-b-PMMA) as stabilizer:rn1. Dispersions of polyurethane and polyurea porous particles for polymer compositesrn2. Dispersions of PMMA and PU particles with PDI dye for study of Single Molecule Spectroscopy Detectionrn3. Dispersions of graphene nanosheets for polymer compositesrnrnIn the first study, highly porous polyurethane and polyurea particles were prepared in a non-aqueous emulsion. The preparation of porous particles consisted of two parts: At first, a system was developed where the emulsion had high stability for the polymerization among diisocyanate, diol and water. In the second part, porous particles were prepared by using two methods fission/fusion and combination by which highly porous particles were obtained. In this study, the applications of porous particles were also investigated where polyurethane particles were tested as filling material for polymer composites and as catalyst carrier for polyethylene polymerization. rnrnIn the second study, PMMA and PU particles from one non-aqueous emulsion were investigated via single molecule fluorescence detection. At first the particles were loaded with PDI dye, which were detected by fluorescence microscopy. The distribution and orientation of the PDI molecules in the particles were successfully observed by Single Molecule Fluorescence Detection. The molecules were homogenously distributed inside of the particles. In addition they had random orientation, meaning that no aggregations of dye molecules were formed. With the results, it could be supposed that the polymer chains were also homogenously distributed in the particles, and that the conformation was relatively flexible. rnrnIn the third part of the study, graphene nanosheets with high surface area were dispersed in an organic solvent with low boiling point and low toxicity, THF, stabilized with a block copolymer PI-b-PMMA. The dispersion was used to prepare polymer composites. It was shown that the modified graphene nanosheets had good compatibility with the PS and PMMA matrices. rn

Runoff Water Quality and Pollutant Mass Loads From Extensive Green Roofs

Green roof mitigation of volume and peak flow-rate of stormwater runoff has been studied extensively. However, due to the common practice of green roof fertilization, there is the potential for introduction of nutrients into local bodies of water. Therefore, this study compares green roof runoff quality with the water quality of precipitation and runoff from a bare shingle roof. The runoff from a demonstration-scale extensive green roof was analyzed during the summer of 2011 for its effect on runoff volume and analyzed during eleven storm events in the fall and winter for concentrations of copper, cadmium, zinc, lead, nitrogen species, total nitrogen, total organic carbon, sulfate, orthophosphate, and other monovalent and divalent ions. The green roof reduced the overall volume of runoff and served as a sink for NO3 - and NH4 +. However, the green roof was also a source for the pollutants PO4 3-, SO4 2-, TOC, cations, and total nitrogen. Metals such as zinc and lead showed trends of higher mass loads in the bare roof runoff than in precipitation and green roof runoff, although results were not statistically significant. The green roof also showed trends, although also not statistically significant, of retaining cadmium and copper. With the green roof serving as a source of phosphorous species and a sink for nitrogen species, and appearing to a retain metals and total volume, the life cycle impact analysis shows minimum impacts from the green roof, when compared with precipitation and bare roof runoff, in all but fresh water eutrophication. Therefore, the best environments to install a green roof may be in coastal environments.

Sediment physicochemical properties condition pollutant association : a multivariate study of polybrominated diphenyl ethers on the Mendoza River irrigation areas

This work is a multidisciplinary environmental study that provides new insights into the relationships between sediment-organic matter characteristics and polybrominated diphenyl ethers (PBDEs) concentration. The aim of the present multivariate study was to correlate factors influencing PBDEs accumulation in sediment by using principal component analysis (PCA). Organic matter studies by Fourier Transform-Infrared spectroscopy and physicochemical analyses (Total Organic Carbon, pH, electrical conductivity) of sediment samples were considered for PCA. Samples were collected from an artificial irrigation network on the Mendoza River irrigation areas. PCA provided a comprehensive analysis of the studied variables, identifying two components that explained 63% of the data variance. Those factors were mainly associated to organic matter degradation degree, which represent a new insight into the relationships between organic matter in sediments and PBDEs fate. In this sense it was possible to determine that not only the content but also the type of organic matter (chemical structure) could be relevant when evaluating PBDEs accumulation and transport in the environment. Typification of organic matter may be a useful tool to predict more feasible areas where PBDE, may accumulate, as well as sediment transportation capability.

Effects of various pollutant mixtures on immune responses of the blue mussel (Mytilus edulis) collected at a salinity gradient in Danish coastal waters, links to supplementary material

The Baltic Sea is a semi-enclosed sea with a steady salinity gradient (3 per mil-30 per mil). Organisms have adapted to such low salinities, but are suspected to be more susceptible to stress. Within the frame of the integrated environmental monitoring BONUS + project "BEAST" the applicability of immune responses of the blue mussel was investigated in Danish coastal waters. The sampling sites were characterised by a salinity range (11-19 per mil) and different mixtures of contaminants (metals, PAHs and POPs), according to chemical analysis of mussel tissues. Variation partitioning (redundancy analysis) was applied to decompose salinity and contamination effects. The results indicated that cellular immune responses (total and differential haemocyte count, phagocytic activity and apoptosis) were mainly influenced by contaminants, whereas humoral factors (haemolytic activity) were mainly impacted by salinity. Hence, cellular immune functions may be suitable as biomarkers in monitoring programmes for the Baltic Sea and other geographic regions with salinity variances of the studied range.

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Pollutant concentrations and Meteorological data classification by Neural Networks

This paper present an environmental contingency forecasting tool based on Neural Networks (NN). Forecasting tool analyzes every hour and daily Sulphur Dioxide (SO2) concentrations and Meteorological data time series. Pollutant concentrations and meteorological variables are self-organized applying a Self-organizing Map (SOM) NN in different classes. Classes are used in training phase of a General Regression Neural Network (GRNN) classifier to provide an air quality forecast. In this case a time series set obtained from Environmental Monitoring Network (EMN) of the city of Salamanca, Guanajuato, México is used. Results verify the potential of this method versus other statistical classification methods and also variables correlation is solved.

Unsupervised method to classify PM10 pollutant concentrations

In this paper a method based mainly on Data Fusion and Artificial Neural Networks to classify one of the most important pollutants such as Particulate Matter less than 10 micrometer in diameter (PM10) concentrations is proposed. The main objective is to classify in two pollution levels (Non-Contingency and Contingency) the pollutant concentration. Pollutant concentrations and meteorological variables have been considered in order to build a Representative Vector (RV) of pollution. RV is used to train an Artificial Neural Network in order to classify pollutant events determined by meteorological variables. In the experiments, real time series gathered from the Automatic Environmental Monitoring Network (AEMN) in Salamanca Guanajuato Mexico have been used. The method can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Caught in the act: gas and stellar velocity dispersions in a fast Quenching compact star-forming galaxy at z ~ 1.7

We present Keck I MOSFIRE spectroscopy in the Y and H bands of GDN-8231, a massive, compact, star-forming galaxy at a redshift of z ~ 1.7. Its spectrum reveals both Hα and [Nii] emission lines and strong Balmer absorption lines. The Hα and Spitzer MIPS 24 μm fluxes are both weak, thus indicating a low star-formation rate of SFR≲5-10 M_⨀ yr−1. This, added to a relatively young age of ~700 Myr measured from the absorption lines, provides the first direct evidence for a distant galaxy being caught in the act of rapidly shutting down its star formation. Such quenching allows GDN-8231 to become a compact, quiescent galaxy, similar to three other galaxies in our sample, by z ~ 1.5. Moreover, the color profile of GDN-8231 shows a bluer center, consistent with the predictions of recent simulations for an early phase of inside-out quenching. Its line-of-sight velocity dispersion for the gas, σ_LOG^gas = 127 ± 32 km s^−1, is nearly 40% smaller than that of its stars, σ_LOG^* = 215 ± 35 km s^−1. High-resolution hydro-simulations of galaxies explain such apparently colder gas kinematics of up to a factor of ~1.5 with rotating disks being viewed at different inclinations and/or centrally concentrated star-forming regions. A clear prediction is that their compact, quiescent descendants preserve some remnant rotation from their star-forming progenitors.

Pollutant emissions during pyrolysis and combustion of waste printed circuit boards, before and after metal removal

The constant increase in the production of electronic devices implies the need for an appropriate management of a growing number of waste electrical and electronic equipment. Thermal treatments represent an interesting alternative to recycle this kind of waste, but particular attention has to be paid to the potential emissions of toxic by-products. In this study, the emissions from thermal degradation of printed circuit boards (with and without metals) have been studied using a laboratory scale reactor, under oxidizing and inert atmosphere at 600 and 850 °C. Apart from carbon oxides, HBr was the main decomposition product, followed by high amounts of methane, ethylene, propylene, phenol and benzene. The maximum formation of PAHs was found in pyrolysis at 850 °C, naphthalene being the most abundant. High levels of 2-, 4-, 2,4-, 2,6- and 2,4,6-bromophenols were found, especially at 600 °C. Emissions of PCDD/Fs and dioxin-like PCBs were quite low and much lower than that of PBDD/Fs, due to the higher bromine content of the samples. Combustion at 600 °C was the run with the highest PBDD/F formation: the total content of eleven 2,3,7,8-substituted congeners (tetra- through heptaBDD/Fs) was 7240 and 3250 ng WHO2005-TEQ/kg sample, corresponding to the sample with and without metals, respectively.

Kinetic Analysis and Pollutant Evolution During Thermal Degradation of Printed Circuit Boards Considering the Effect of Metals

Paper submitted to the 7th International Symposium on Feedstock Recycling of Polymeric Materials (7th ISFR 2013), New Delhi, India, 23-26 October 2013.

Pollutant Formation During the Thermal Decomposition of Electrical and Electronic Wastes

Paper submitted to the 7th International Symposium on Feedstock Recycling of Polymeric Materials (7th ISFR 2013), New Delhi, India, 23-26 October 2013.

Pollutant emissions during the pyrolysis and combustion of flexible polyurethane foam

Thermal decomposition of flexible polyurethane foam (FPUF) was studied under nitrogen and air atmospheres at 550 °C and 850 °C using a laboratory scale reactor to analyse the evolved products. Ammonia, hydrogen cyanide and nitrile compounds were obtained in high yields in pyrolysis at the lower temperature, whereas at 850 °C polycyclic aromatic hydrocarbons (PAHs) and other semivolatile compounds, especially compounds containing nitrogen (benzonitrile, aniline, quinolone and indene) were the most abundant products. Different behaviour was observed in the evolution of polychlorodibenzo-p-dioxins and furans (PCDD/Fs) at 550 °C and 850 °C. At 550 °C, the less chlorinated congeners, mainly PCDF, were more abundant. Contrarily, at 850 °C the most chlorinated PCDD were dominant. In addition, the total yields of PCDD/Fs in the pyrolysis and combustion runs at 850 °C were low and quite similar.

A Fortran program for computing the pollutant standards index (PSI) /

Mode of access: Internet.

Field testing, application of combustion modifications to control pollutant emissions from industrial boilers : phase II /

Mode of access: Internet.