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Abstract. Meteorological normalisation is a technique which accounts for changes in meteorology over time in an air quality time series. Controlling for such changes helps support robust trend analysis because there is more certainty that the observed trends are due to changes in emissions or chemistry, not changes in meteorology. Predictive random forest models (RF; a decision tree machine learning technique) were grown for 31 air quality monitoring sites in Switzerland using surface meteorological, synoptic scale, boundary layer height, and time variables to explain daily PM 10 concentrations. The RF models were used to calculate meteorologically normalised trends which were formally tested and evaluated using the Theil-Sen estimator. Between 1997 and 2016, significantly decreasing normalised PM 10 trends ranged between −0.09 and −1.16 µg m −3 yr −1 with urban traffic sites experiencing the greatest mean decrease in PM 10 concentrations at −0.77 µg m −3 yr −1 . Similar magnitudes have been reported for normalised PM 10 trends for earlier time periods in Switzerland which indicates PM 10 concentrations are continuing to decrease at similar rates as in the past. The ability for RF models to be interpreted was leveraged using partial dependence plots to explain the observed trends and relevant physical and chemical processes influencing PM 10 concentrations. Notably, two regimes were suggested by the models which cause elevated PM 10 concentrations in Switzerland: one related to poor dispersion conditions and a second resulting from high rates of secondary PM generation in deep, photochemically active boundary layers. The RF meteorological normalisation process was found to be robust, user friendly and simple to implement, and readily interpretable which suggests the technique could be useful in many air quality exploratory data analysis situations.

Abstract. The Tropospheric ORganic CHemistry experiment (TORCH) took place during the heatwave of summer 2003 at Writtle College, a site 2 miles west of Chelmsford in Essex and 25 miles north east of London. The experiment was one of the most highly instrumented to date. A combination of a large number of days of simultaneous, collocated measurements, a consequent wealth of model constraints and a highly detailed chemical mechanism, allowed the atmospheric chemistry of this site to be studied in detail. Between 25 July and 31 August, the concentrations of the hydroxyl radical and the hydroperoxy radical were measured using laser-induced fluorescence at low pressure and the sum of peroxy radicals was measured using the peroxy radical chemical amplifier technique. The concentrations of the radical species were predicted using a zero-dimensional box model based on the Master Chemical Mechanism version 3.1, which was constrained with the observed concentrations of relatively long-lived species. The model included a detailed parameterisation to account for heterogeneous loss of hydroperoxy radicals onto aerosol particles. Quantilequantile plots were used to assess the model performance in respect of the measured radical concentrations. On average, measured hydroxyl radical concentrations were overpredicted by 24%. Modelled and measured hydroperoxy radical concentrations agreed very well, with the model overpredicting on average by only 7%. The sum of peroxy radicals was under-predicted when compared with the respective measurements by 22%. Initiation via OH was dominatedCorrespondence to: N. Carslaw (nc12@york.ac.uk) by the reactions of excited oxygen atoms with water, nitrous acid photolysis and the ozone reaction with alkene species. Photolysis of aldehyde species was the main route for initiation via HO 2 and RO 2 . Termination, under all conditions, primarily involved reactions with NO x for OH and heterogeneous chemistry on aerosol surfaces for HO 2 . The OH chain length varied between 2 and 8 cycles, the longer chain lengths occurring before and after the most polluted part of the campaign. Peak local ozone production of 17 ppb hr −1 occurred on 3 and 5 August, signifying the importance of local chemical processes to ozone production on these days. On the whole, agreement between model and measured radicals is good, giving confidence that our understanding of atmospheres influenced by nearby urban sources is adequate.

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