Pollution trends using bark of morus alba in the cities of buenos aires and mendoza (Argentina)

A comparative study of elements deposited on tree bark was carried out for urban and periurban areas of two of the most important cities in Argentina. The content of Fe, Mg, Al, Mn, Zn, Pb, Ba, Cr, Hg, Cu, Ni, Cd and Sb was determined by inductively coupled plasma atomic emission spectrometry (ICP-OES) in Morus alba tree bark collected in the cities of Buenos Aires and Mendoza. The main air pollutants detected in the Buenos Aires urban area were Ba, Cr, Cu and Ni and indicate significative difference from the Mendoza urban and periurban areas. Significantly, higher concentrations of Zn, Ba, Cr and Cu were recorded in the periurban area of the city of Buenos Aires than in Mendoza. Bark samples were strongly influenced by dust and show Al, Fe, Mg and other element accumulations that indicate that soil particles were carried out by wind. Elements like Ba and Zn, commonly linked to traffic emissions, showed the highest concentrations in the Buenos Aires metropolitan area, possibly due to more intensive vehicular traffic. Our results indicated that intensity of vehicular traffic and not city structure is responsible for air pollution.

Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

ABSTRACTChanges in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.