The prediction is valid for any emission or process data that can be continuously measured and included in the initial training dataset that can be correlated with the available process data. The model is initially developed with NOx, CO, CO2, O2, SO2, and total hydrocarbon data. Particulate, H2S, NH3, PM10, PM2.5, opacity and other emission parameters can also be predicted with the statistical hybrid engine.
The accuracy of the prediction for NOx mass emission rates from gas turbines and gas-fired boilers have been the most extensively studied and demonstrated to date. Other pollutant emission rates that have been established to be accurately modeled by SmartCEMS®-60 including CO, SO2, and hydrocarbon emission rates, as well as, exhaust gas diluent O2 and CO2. Other turbine or boiler parameters such as exhaust temperature and flow rate have also been evaluated and show good accuracy. Hydrocarbon, CO, SO2, NOx, and O2 have also been demonstrated to be accurately modeled from sewage sludge incinerators and industrial boilers.