Data Processing Tools for Measuring Concentrations of Greenhouse Gas Carbon Dioxide in the Atmospheric Surface Layer
Introduction. The total anthropogenic greenhouse gas emissions are estimated in CO2 equivalent. The need to calculate a carbon tax and determine quotas for CO2 emissions define the practical significance of measuring and calculating carbon dioxide concentrations. Taking into account the high cost of control and measuring equipment and its limited list, the use of calculation methods for determining carbon dioxide concentrations is promising. Direct calculation of carbon dioxide concentrations at this stage is not feasible due to the lack of detailed information on the parameters of emissions of the greenhouse gas in the context of each source. The aim of the research is to develop a neural network method for calculating carbon dioxide concentrations with the use of the hybrid model. Research method. To obtain carbon dioxide concentrations, a neural network of the third level was designed. This network takes into account the transformation of carbon monoxide into carbon dioxide. The transformation coefficient and the measured ozone concentration, which characterize the intensity of secondary reactions in the atmosphere, were used as network predictors together with the concentration of carbon monoxide. To train the neural network, there were also used the results of measurements performed on the automatic air pollution monitoring station (AAPMS). Findings. Approbation of the model was carried out for Kazan. The data array was compiled from the results of measurements of meteorological conditions and concentrations of pollutants at two AAPMS in Kazan. Then data array was extended by the results of calculations of carbon monoxide concentrations in the “Ecolog-Gorod” software. Next, the calculated values were corrected with the use a neural network model of the MLP type (Multi-Layer direct propagation Perceptron). At the third level of the model, carbon dioxide concentrations are calculated. The accuracy of the model was above 83%. A hybrid neural network model, after appropriate training, can be used to calculate carbon dioxide concentrations in the atmosphere of various industrial cities on the territory of the Russian Federation.