Ana Paula Barbosa Rodrigues de Freitas

Chemometrics: Theory and Application

This chapter aims to present a chemometrics as important area in chemistry to be able to help work with many among of data obtained in analysis. The term chemometrics was introduced in initial 70th years by Svant Wold (Swede) and Bruce Kowalski (USA). According International Chemometrics Society, founded in 1974, the accept definition to chemometrics is (i) the chemical discipline that uses mathematical and statistical methods to design or select optimal measurement procedures and experiments (ii) to provide maximum chemical information by analyzing chemical data [1]. When the study involving many variable became the study in a multivariate analysis, so it is necessary to building a typical matrix and is normal to do a pre-processing. Pre-processing is a procedure to adjust the different factors with different units in values than allow give for each factor the same change to contribute to the model. After, next step is usually the Pattern Recognition method, to find any similarity in your data. In This method is common using the unsupervised group where there are the HCA and PCA analysis and the supervised group where there is the KNN. The HCA analysis (Hierarchical Cluster Analysis) is used to examine the distance among the samples in two dimensional plot (dendogram) and cluster samples with similarity. (Figure 1). Now PCA analysis (Principal Component analysis) is used to try decrease the size data set, without lost information about samples (Figure 2) and KNN used to classify samples using cluster previously know [2].

Contributions of Multivariate Statistics in Oil and Gas Industry

Pasquini and Bueno (2007) have proposed a new approach to predict the true boiling point of oil and its degree API (American Petroleum Institute) a measure of the relative density of liquids by Partial Least Squares (PLS) and Artificial Neural Networks (ANN). Samples of mixtures oil were obtained from various producing regions of Brazil and abroad. In this application, the models obtained by the PLS method were superior to neural networks. The short time required for prediction the properties justifies the proposed of characterization the oil quicker to monitor refining processes.

Taguchi Method Applied to Environmental Engineering

Over the last decades, environmental concerns have become more critical and frequent. Thisis, mainly, due to population growth and the increase of industrial activities in which anthro‐pogenic actions have reached catastrophic proportions resulting in changes of soil, air, andwater quality [1].Environmental pollution by industrial effluent is being characterized as one of the major causesof the aggravation of this problem. Residues, in general, produce diversified compounds,containing, frequently, pollutants that are toxic and resistant to conventional treatments suchas coagulation/flocculation or biodegradation [2], and they are eventually discharged, in mostof the cases, in an inadequate way causing severe damages. Regarding the environmentalproblem, researchers were driven to study the feasibility of new techniques and methodolo‐gies, as well as, the emission and pollutant discharge control. In order to apply the pollutioncontrol and to attend environmental legislation, patterns and quality indicators were estab‐lished. In terms of water quality: oxygen concentration, phenols, Hg, pH, temperature, amongother requirements [3].Companies search for new environmental alternatives to treat generated residuals. Theenvironmental reality is demanding for further actions to mitigate industrial impacts on water.Therefore, water treatment has become a mandatory investment to industries, institutions, andothers with the aim to attending environmental laws, as well as ISO 14000 series.

Multivariate Modeling in Quality Control of Viscosity in Fuel: An Application in Oil Industry

Out of specification values can decrease the fuel volatilization, thus implying, in an incomplete combustion (Pontes et al., 2010). This physicochemical property can vary significantly with the modification of the cast during the processing of crude in a refinery (Figure 1), maintaining the same conditions of production control, which compromises the quality standards. This leads to the need to determine the viscosity or provide it as often as possible in lieu of performing the traditional point analysis in the laboratory that can take long time.

Chemometric Methods for the Optimization of the Advanced Oxidation Processes for the Treatment of Drinking and Wastewater

Advanced Oxidative Processes (AOP) have been successfully employed as efficient water treatment methods. The utilization of AOP on drinking and wastewater represents currently an alternative to costly, hazardous, and slow processes. In order to further establish the ground basis for AOP in water safety and security, reliable and consistent methods of analysis are required. As an alternative to basic statistical methods, which may not successfully describe and forecast the application of a given treatment methodology of water, the use of chemometrics has increased significantly over the past decades. Chemometric analyses are an intersection between analytical chemistry and applied statistical models in order to predict and extract information from a given condition. This chapter introduces the concepts of chemometrics in environmental engineering issues and the utilization of experimental design to efficiently analyze experimental data in environmental samples. Two case studies are presented to demonstrate the importance of chemometrics in water analyses: (1) considering a Taguchi L16 experimental design, and an optimization study using Response Surface Methodology, to evaluate photo-Fenton and ozone AOP-based treatment on an effluent with high concentration of organic matter; (2) using a Taguchi L9 array to evaluate the combination of photocatalytic degradation and AOP of an industrial effluent. The results showed in this chapter demonstrate how a given statistical method can be successfully employed within the intersection of environmental analyses and water issues.

Multivariate Analysis in Advanced Oxidation Process

Industrial processes can create a wide variety of chemicals that pollute the air and water, with adverse impacts to ecosystems and humans. These impacts are caused by the polluting compounds that have toxic, carcinogenic, and also mutagenic properties (Busca et al., 2008). The treatment of wastewater containing phenolic compounds can be accomplished using applied principles of chemical oxidation, settling, membrane filtration, osmosis, ion, precipitation, and coagulation among other methods (Lin; Juang, 2009).