Prediction of global warming potential and carbon tax of a natural gas-fired plant

Abstract

Industrial activities, including the process of power generation from thermal plants, are inevitably associated with the generation of gaseous wastes and particulate matters. Industrial activities, therefore, contribute largely to the emission of environmental pollutants. In addition to causing environmental degradation, the emission of pollutants, particularly greenhouse gases, have far-reaching social negative externalities, mainly in the area of unconducive temperature rise and adverse climatic impact. The unintended impacts of industrial emissions have motivated the development of plans and strategies for their abatement. In this study, predictive models of the global warming potential and carbon tax of the gaseous emission at various fuel consumption levels and different air–fuel ratio for the combustion process in a thermal power plant were developed. It is expected that the models serve as a veritable tool for projecting the environmental & economic costs of natural gas burning and optimizing the process of the fuel combustion for lower greenhouse gas emissions.

Keywords

• Industrial activities
• Energy conversion
• Global warming
• Emission reduction
• Carbon tax
• Artificial intelligence