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Accurately predicting air pollutant levels is very important for mitigating their effects. Prediction models usually fail to predict sudden large increases or decreases in pollutant levels. Conventional measures for the assessment of the performance of air pollutant prediction models provide an overall assessment of model behavior, but do not explicitly address model behavior when large changes are observed. In our work, we propose a method to automatically label the observed large changes. Wedoi:10.3390/atmos13091456 fatcat:x4kgmq7f7fhyheatvxjmmtip3i