Natural Membranes for Application in Biomedical Devices

Polymers from natural sources are particularly useful as biomaterials for medical devices applications. In this study, the results of characterization of a gelatin network electrolyte doped with europium triflate (Eu(CF3SO3)(3)) are described. The unusual electronic properties of the trivalent lanthanide ions make them well suited as luminescent reporter groups, with many applications in biotechnology. Samples of solvent-free electrolytes were prepared with a range of guest salt concentration. Materials based on Eu(CF3SO3)(3) were obtained as mechanically robust, flexible, transparent, and completely amorphous films. Samples were characterized by thermal analysis (thermo-gravimetry analysis (TGA) and differential scanning calorimetry (DSC), electrochemical stability, scanning electronmicroscopy (SEM), and photoluminescence spectroscopy.

Urban air pollution: a representative survey of PM2.5 mass concentrations in six Brazilian cities

In urban areas of Brazil, vehicle emissions are the principal source of fine particulate matter (PM2.5). The World Health Organization air quality guidelines state that the annual mean concentration of PM2.5 should be below 10 mu g m(-3). In a collaboration of Brazilian institutions, coordinated by the University of Sao Paulo School of Medicine and conducted from June 2007 to August 2008, PM2.5 mass was monitored at sites with high traffic volumes in six Brazilian state capitals. We employed gravimetry to determine PM2.5 mass concentrations, reflectance to quantify black carbon concentrations, X-ray fluorescence to characterize elemental composition, and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations and proportions of black carbon (BC) in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Recife, and Porto Alegre were 28.1 +/- 13.6 mu g m(-3) (38% BC), 17.2 +/- 11.2 mu g m(-3) (20% BC), 14.7 +/- 7.7 mu g m(-3) (31% BC), 14.4 +/- 9.5 mu g m(-3) (30% BC), 7.3 +/- 3.1 mu g m(-3) (26% BC), and 13.4 +/- 9.9 mu g m(-3) (26% BC), respectively. Sulfur and minerals (Al, Si, Ca, and Fe), derived from fuel combustion and soil resuspension, respectively, were the principal elements of the PM2.5 mass. We discuss the long-term health effects for each metropolitan region in terms of excess mortality risk, which translates to greater health care expenditures. This information could prove useful to decision makers at local environmental agencies.

Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities

In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM2.5 samples, employing gravimetry to determine PM2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 mu g/m(3), respectively. In Sao Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM2.5 mass. We used receptor models to identify distinct source-related PM2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-a-vis health care costs.