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  1. Home
  2. Browse by Author

Browsing by Author "Letelier, MV"

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    Aging of copper pipes by drinking water
    (AMER WATER WORKS ASSOC, 2001) Lagos, GE; Cuadrado, CA; Letelier, MV
    Thermodynamic models were used to correlate experimental and field data for the concentrations of copper (Cu), anions, and cations in drinking water with Cu-containing scales on the inner walls of pipes. This study focused special attention on the aging processes of these scales. Precipitation and dissolution were predicted to be the main aging causes for Cu scales present on the inner walls of pipes. When data were grouped by the solid that controls solubility, the average 8-h stagnant Cu concentration in drinking water was found to decrease linearly with average pipe age. For these average values, langite was the most soluble and youngest film, followed in both solubility and age by cupric hydroxide, azurite, brochantite, malachite, and tenorite. The more stable solids-malachite and tenorite-were 8 and 16 times less soluble, respectively, than the most soluble solid, langite. Scales usually contained more than one compound, a finding that was attributed to temperature changes, variability of water composition, long stagnation periods, and aging. During the aging process, parts of a young scale surface area may be covered and blocked for further reaction by a precipitate. During long stagnation periods, such factors as changes in pH, oxygen, and carbon dioxide concentrations and precipitation of calcium solids may induce a different Cu compound precipitate.
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    Forecasting ozone daily maximum levels at Santiago, Chile
    (PERGAMON-ELSEVIER SCIENCE LTD, 1998) Jorquera, H; Perez, R; Cipriano, A; Espejo, A; Letelier, MV; Acuna, G
    In major urban areas, air pollution impact on health is serious enough to include it in the group of meteorological variables that are forecast daily. This work focusses on the comparison of different forecasting systems for daily maximum ozone levels at Santiago, Chile. The modelling tools used for these systems were linear time series, artificial neural networks and fuzzy models. The structure of the forecasting model was derived from basic principles and it includes a combination of persistence and daily maximum air temperature as input variables. Assessment of the models is based on two indices: their ability to forecast well an episode, and their tendency to forecast an episode that did not occur at the end (a false positive). All the models tried in this work showed good forecasting performance, with 70-95% of successful forecasts at two monitor sites: Downtown (moderate impacts) and Eastern (downwind, highest impacts). The number of false positives was not negligible, but this may be improved by expressing the forecast in broad classes:low, average, high, very high impacts; the fuzzy model was the most reliable forecast, with the lowest number of false positives among the different models evaluated. The quality of the results and the dynamics of ozone formation suggest the use of a forecast to warn people about excessive exposure during episodic days at Santiago. (C) 1998 Elsevier Science Ltd. All rights reserved.

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