New regulations about greenhouse gas emissions force governmental and environmental organizations around the world to look for efficient monitoring tools in order to manage their contribution to global warming. Monitoring and, above all, quantification of the amount of released carbon dioxide (CO2) and other greenhouse gases in the environment from industries may present a challenge due to the technical difficulties associated with sampling or site access. The Telops Hyper-Cam, an infrared hyperspectral imager, offers the possibility to detect, identify and quantifiy greenhouse gases generated by industrial facilities. This paper demonstrates how standofff quantification of greenhouse gas emissions can be accurately achieved using a combination of high resolution hyperspectral imaging and signal processing algorithms.
The increasing presence of greenhouse gases such as carbon dioxide (CO2) and nitrous oxide (N2O) raise major concerns worldwide due to their potential effect on global warming. As a global environmental effort, most countries try to reduce their greenhouse gas emissions. In such context, the need for a monitoring tool capable of efficient identification and quantification of these emissions is mandatory.
The main entropic contribution of CO2 into the atmosphere comes from power stations, such as fossil fuel power plants. Coal combustion, as for most fossil fuels, generates CO2 and water vapor (H20) as well as nitrogen oxides (NOX) and sulfur oxides (SOX) as by- products. The overall amount of generated product depends on several parameters such as the fuel grade and the efficiency of the burning technology. Therefore, versatile tools are needed for the quantification of the gas emissions. Not all gas exhausts are equipped with continuous monitoring emission systems (CEMS). In addition, values reported by these devices are not always accurate due to interference in the complex gas mixture of smokestacks. Direct sampling of the emission gases may present itself as a complex and costly task as most of these structures are out of reach. Remote sensing presents a distinct advantage in this case as well as an excellent alternative verification method, since remote sensing techniques do not require any sampling system.