|Abstract Title:||Advanced remote sensing solutions accommodating petrochemical/chemical industrial monitoring needs and challenges|
|Presenter Name:||Mr Gilad Shpitzer|
|Session Choice:||Fence line monitoring & measurement of fugitive/diffuse emissions|
Abstract Information :
The petrochemical and chemical industries are facing new challenges. Extended focus, new legislation, regulations and better standards have been presented by governments and regulators for air quality management. New solutions are now required to provide high sensitivity, low detection limit, continuous and spatial monitoring as a real time control and prevention tool for fugitive emissions.
In order to meet these challenges automation of remote sensing with Open Path FTIR have been selected for development. The gas analysis is based on USEPA method TO-161 and ASTM method E1865-97(2013) together with optical remote sensing for emission characterization from non-point source -method USEPA MTO-10. The innovation of the automatic technology is the "Spectral averaging" technique which has been developed and got implemented to improve the measurement sensitivity (MDL detection limit). The main goal of using spectral averaging is to create a clean background spectrum by reducing the "noise" for each measured data. The best suitability of different spectral averaging times for short term-high concentration vs long term- low concentration events was researched using the FTIR and a real time, long term measurement protocol along the fence lines and will be presented. The algorithm has been proved to reduce "background noise" and improve the performance of the FTIR analysis for a lower detection limit per each measured compound.
The major impact of human errors and equipment failures on the total annual emissions during short or long term events occur in the polluting facilities had been evaluated . Case studies, data sets and results from various campaigns would be demonstrated. Continuous spatial monitoring with a quality feature of source location had been proved to be a significant way to prevent emergencies, assist with a root cause analysis and reduce the overall annual emission rate. Examples from live projects will be presented.