A data-driven approach for predicting and monitoring nitrogen oxides emissions of natural gas CCGT in power plants with neural networks

Air pollutants contribute to global warming and climate change. Nitrogen oxides emissions have been increasing by 33% from 1990 until 2021 in upper-middle-income countries and by 11% in low-income countries. In total, in Portugal 40.7% of NOx emissions were due to road transport, 24.3% were from Industrial combustion, 10.7% of emissions were from other mobile sources and 9.1% of NOx emissions were from power stations. Advancements in data learning, optimization of algorithms and predictions enable the development of neural networks and computing. In this work it was developed the monitoring and prediction of nitrogen oxides emissions with neural networks considering experimental data from a natural gas power plant.