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CITGO

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CITGO proposes to develop an alternative emissions monitoring system at its Corpus Christi, Texas facility. The Parametric Emission Monitoring (PEM) system utilizes neural network mathematical models to evaluate and predict nitrogen oxide (NOx) and carbon monoxide (CO) emissions from fired sources such as heaters and boilers. CITGO intends to link the computer model directly to central plant operations, allowing them to monitor boiler emissions and compare the data to the model's predictions. CITGO believes that analysis of the information on emissions parameters generated by the model will assist in minimizing Nox and CO emission levels. CITGO intends to begin the project with a pilot study on two boilers, whereby they will predict Nox emissions, then develop and use a computer program to optimize boiler firing and minimize NOx emissions. In order to implement the project, CITGO seeks negotiation of a NOx and CO emissions bubble for this facility, which would provide flexibility for testing emissions parameters. In addition, CITGO seeks relief from the Clean Air Act's (CAA), Prevention of Significant Deterioration (PSD)-required, ground-level monitoring equipment, and proposes to demonstrate reduced emissions with computer models instead.


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