Detecting an abnormality in a recovery boiler using dynamic multivariate data analysis with parallel coordinate plots

Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

Chronic contamination assessment integrating biomarkers' responses in transplanted mussels-A seasonal monitoring

This study aimed to provide the first biomonitoring integrating biomarkers and bioaccumulation data in Sao Paulo coast, Brazil and, for this purpose, a battery of biomarkers of defense mechanisms was analyzed and linked to contaminants' body burden in a weigh-of-evidence approach. The brown mussel Perna perna was selected to be transplanted from a farming area (Caraguatatuba) to four possibly polluted sites: Engenho D'Agua, DTCS (Dutos e Terminais do Centro-Oeste de Sao Paulo) oil terminal (Sao Sebastiao zone), Palmas Island, and Itaipu (It; Santos Bay zone). After 3 months of exposure in each season, mussels were recollected and the cytochrome P4501A (CYP1A)- and CYP3A-like activities, glutathione-S-transferase and antioxidants enzymes (catalase, glutathione peroxidase, and glutathione reductase) were analyzed in gills. The concentrations of polycyclic aromatic hydrocarbons, linear alkylbenzenes, and nonessential metals (Cr, Cd, Pb, and Hg) in whole tissue were also analyzed and data were linked to biomarkers' responses by multivariate analysis (principal component analysisfactor analysis). A representation of estimated factor scores was performed to confirm the factor descriptions and to characterize the studied stations. Biomarkers exhibited most significant alterations all year long in mussels transplanted to It, located at Santos Bay zone, where bioaccumulation of organic and inorganic compounds was detected. This integrated approach using transplanted mussels showed satisfactory results, pointing out differences between sites, seasons, and critical areas, which could be related to land-based contaminants' sources. The influence of natural factors and other contaminants (e.g., pharmaceuticals) on biomarkers' responses are also discussed.

A Single Statistic for Monitoring the Covariance Matrix of Bivariate Processes

In this article, we present a new control chart for monitoring the covariance matrix in a bivariate process. In this method, n observations of the two variables were considered as if they came from a single variable (as a sample of 2n observations), and a sample variance was calculated. This statistic was used to build a new control chart specifically as a VMIX chart. The performance of the new control chart was compared with its main competitors: the generalized sampled variance chart, the likelihood ratio test, Nagao's test, probability integral transformation (v(t)), and the recently proposed VMAX chart. Among these statistics, only the VMAX chart was competitive with the VMIX chart. For shifts in both variances, the VMIX chart outperformed VMAX; however, VMAX showed better performance for large shifts (higher than 10%) in one variance.

Taxonomic sufficiency of polychaete taxocenes for estuary monitoring

The polychaetes assemblage structure was used in order to investigate taxonomic sufficiency in a heavily polluted tropical bay. Species abundance was aggregated into progressively higher taxa matrices (genus, family, order) and was analyzed using univariate and multivariate techniques. Polychaetes distribution in Guanabara Bay (GB) was in accordance with a pollution gradient, probably ruled by the organic enrichment, consequent effects of hypoxia and altered redox conditions coupled with prevailing patterns of circulation. Within the sectors of GB, an increasing gradient in species richness and occurrence was observed, ranging from the azoic and impoverished stations in the inner sector to a well-structured community in terms of species composition and abundance inhabiting the outer sector. Multivariate statistical analysis showed similar results when species were aggregated into genera and families, while greater difference occurred at coarser taxonomic identification (order). The literature about taxonomic sufficiency has demonstrated that faunal patterns at different taxonomic levels tend to become similar with increased pollution. In GB, an analysis carried out solely at family level is perfectly adequate to describe the environmental gradient, considered a useful tool for a quick environmental assessment. (C) 2011 Elsevier Ltd. All rights reserved.