Weather (meteorology) has a strong effect on air quality; if not accounted for, there is uncertainty surrounding what drives features in air quality time series. We present a machine learning approach to account for meteorology using PM₁₀ data in Switzerland. With the exception of one site, all Swiss normalised PM₁₀ trends were found to significantly decrease, which validates air quality management efforts. The machine learning models were interpreted to investigate interesting processes.