A study was conducted with a view to determining the steps to be taken in order to control the Bacharach opacity of smoke released by different types of engines powered by fuel oil through the same chimney. A statistical model was constructed to relate Bacharach opacity to the operational parameters of the burning equipment on the basis of information recorded during its routine functioning over a period of about one year, with no laboratory experiments nor intentional alteration of such parameters. Different chemometric tools were applied to the data recorded over a period long enough to ensure a good model. Owing to the high complexity of the data handled (equipment parameters, fuel oil properties, operating conditions, etc. ), the model was constructed by using different tools that were tested in order of increasing complexity. Thus, a Principal Component Analysis (PCA) was initially conducted on the variables defining the different types of fuel oil used in order to suppress their high correlation. The scores obtained from this analysis were used as the fuel data in the subsequent steps. Owing to the high complexity of the parameters involved, linear regression methods were not functional, so the non-linear regression method Alternating Conditional Expectations (ACE) had to be used instead to determine the influence of these parameters on Bacharach opacity. After the model was constructed, the parameters that govern opacity were determined and the model was experimentally validated by exploring the variables that can be modified at plant level (viz. the combination of Conradson coke and asphaltenes in the fuel, the oil viscosity at burner and the proportion of oxygen in the furnace). Changes in these variables were found to alter the properties of the stack; also, the predictions of the ACE model were confirmed. Consequently, the proposed methodology allows the effective control of smoke released by the equipment.
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