Computer-aided method for generating training data for a neural network, wherein the neural network is designed to determine a pollutant concentration at a measurement station from at least one pollutant emission, characterized by the following steps: - providing at least one measurement series of the pollutant concentration containing at least one measured value that is above a defined threshold value; - providing at least one measurement series for a physical measured variable related to the measured pollutant concentration, which is a temperature, a wind speed and/or a wind direction, a traffic level, and/or chemical substance concentrations, the measured pollutant concentration being dependent on the measured variable; - providing a transmission model, wherein the transmission model models a relationship between the pollutant emission, the measured variable and the pollutant immission at the measurement station; - computing a first value I 0 of the pollutant immission at the measurement station by means of the transmission model from the pollutant emission, this being accomplished by using at least one measured value of the measured variable that is related to a value C 0 of the provided measured pollutant concentration; - computing a second value I 1 of the pollutant immission at the measurement station by means of the transmission model from the pollutant emission, this being accomplished by numerically altering the measured value of the measured variable that is used for computing the first value I 0 of the pollutant immission; and - generating a synthetic measurement series as training data by means of an alteration Δ C of the value C 0 of the provided measured measurement series of the pollutant concentrations, the alteration Δ C of the at least one value C 0 of the provided measurement series of the pollutant concentration being made by means of Δ C / C 0 = α ( I 1 - I 0) / I 0, where α is a traffic-related proportion of the pollutant concentration. - providing at least one measurement series of the pollutant concentration containing at least one measured value that is above a defined threshold value; - providing at least one measurement series for a physical measured variable related to the measured pollutant concentration, which is a temperature, a wind speed and/or a wind direction, a traffic level, and/or chemical substance concentrations, the measured pollutant concentration being dependent on the measured variable; - providing a transmission model, wherein the transmission model models a relationship between the pollutant emission, the measured variable and the pollutant immission at the measurement station; - computing a first value I 0 of the pollutant immission at the measurement station by means of the transmission model from the pollutant emission, this being accomplished by using at least one measured value of the measured variable that is related to a value C 0 of the provided measured pollutant concentration; - computing a second value I 1 of the pollutant immission at the measurement station by means of the transmission model from the pollutant emission, this being accomplished by numerically altering the measured value of the measured variable that is used for computing the first value I 0 of the pollutant immission; and - generating a synthetic measurement series as training data by means of an alteration Δ C of the value C 0 of the provided measured measurement series of the pollutant concentrations, the alteration Δ C of the at least one value C 0 of the provided measurement series of the pollutant concentration being made by means of Δ C / C 0 = α ( I 1 - I 0) / I 0, where α is a traffic-related proportion of the pollutant concentration.