Excess cohesive particulate matter removal at upflow settling conditions

Abstract

in Wiley InterScience (www.interscience.wiley.com).The magnitude of excess particulate matter separation from a flocculated suspension at upflow settling conditions was predicted from the concentration distribution of batch settling data. The settling data pairs were fitted to modified population-growth model. Settling surfaces at upflow operation were increased by inlaying pipes into the column and inclining it for 508, 608, 70 and 808 coinciding with 0.5563, 0.7152, 1.0455 and 2.0594 mm/s decreased surface hydraulic loading rates, respectively. The respective removal ratios observed at the applied loadings were 0.878, 0.848, 0.756 and 0.520, while the corresponding predicted efficiencies by mean value method were 0.865, 0.831, 0.773 and 0.512, respectively. It was demonstrated that removal predictions obtained from the batch settling tests were quite compatible with the observed removals of actual upflow operation. The investigation also demonstrated that concentration distribution of batch settling data heads successfully to predict the excess particulate matter removal at upflow settling.

Preliminary Physical Chemical Characterization of River Waters and Sediments Affected by Copper Mining Activity in Central Chile: Application of Multivariate Analysis

“…Multivariate methods to analyze environmental data constitute an increasingly important part of statistics, because they allow an easier interpretation of the results. [22][23][24] Principal component analysis (PCA) PCA was applied in order to obtain a statistical correlation among the different components of the environmental matrices analyzed (river waters and sediments). The application of PCA allowed reducing the number of the variables in a few components with minimum loss of information, which was obtained by the linear combination of all the variables in consideration.…”