Oil boom,a blessing for Mexico?

GeoJournal - The oil discoveries in Southern Mexico are now thought to be linked in one vast field a geological blessing that could catapult Mexico as the world's second largest oil producer....     

Permeability and compression characteristics of municipal solid waste samples

Four series of laboratory tests were conducted to evaluate the permeability and compression characteristics of municipal solid waste (MSW) samples. While the two series of tests were conducted using a conventional small-scale consolidometer, the two others were conducted in a large-scale consolidometer specially constructed for this study. In each consolidometer, the MSW samples were tested at two different moisture contents, i.e., original moisture content and field capacity. A scale effect between the two consolidometers with different sizes was investigated. The tests were carried out on samples reconsolidated to pressures of 123, 246, and 369 kPa. Time settlement data gathered from each load increment were employed to plot strain versus log-time graphs. The data acquired from the compression tests were used to back calculate primary and secondary compression indices. The consolidometers were later adapted for permeability experiments. The values of indices and the coefficient of compressibility for the MSW samples tested were within a relatively narrow range despite the size of the consolidometer and the different moisture contents of the specimens tested. The values of the coefficient of permeability were within a band of two orders of magnitude (10⁻⁶–10⁻⁴ m/s). The data presented in this paper agreed very well with the data reported by previous researchers. It was concluded that the scale effect in the compression behavior was significant. However, there was usually no linear relationship between the results obtained in the tests.     

Studying the spatial and temporal distribution of SO2 in an urban area by principal component factor analysis

The spatial distribution of SO₂ concentration is studied as measured at nine locations in the urban area of Valladolid, using the principal component factor analysis. The three retained components are interpreted as caused by different types of sources. Also the temporal variation of SO₂ concentrations has been studied at each location in relation to 21 meteorological parameters and to a persistence index of the concentrations. To avoid the use of correlated parameters the authors have at the same time applied the principal component factor analysis on 21 variables. Then the multiple linear regression was fitted between the SO₂ concentrations measured at each location, and the seven retained meteorological components. In this way the interpretation of the spatial distribution could be confirmed.