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Haze formation involves many interacting factors, such as secondary aerosol formation, unfavourable synoptic conditions and regional transport. The interaction between these factors complicates scientific understanding of the mechanism behind haze formation. In this study, we investigated the factors resulting in haze events in Longyou, a city located in a basin in China. Aerosol samples of PM 2.5 were collected for subsequent chemical composition analysis between 11 January and 5 February 2018. The impacts of wind on PM 2.5 , SO 2 and NO 2 concentrations were analysed. Besides, the origin of air parcels and potential sources of PM 2.5 were analysed by backward trajectory, potential source contribution function (PSCF) and concentration-weighted trajectories (CWT). Among the water-soluble ions identified, NO 3 − had the highest concentration, with further analysis demonstrating the haze evolution was mainly driven by the reactions involving NO 3 − formation. The dramatic increase of nitrate is mainly due to the homogeneous reaction of nitric acid with ammonia, while sulfate is likely due to heterogeneous reactions of NO 2 , SO 2 and NH 3. The average wind speed was less than 2 m/s during the aerosol sampling period, which could be considered as a stagnant state. Pollutants emitted by industrial area located in the northeast Longyou were probably brought to observation sites by continuous wind from northeast and accumulated gradually. Air parcels originating from the northeast of Zhejiang province also had large effects on haze pollution in Longyou. Together, our results showed that rapid secondary aerosol formation and unfavourable synoptic conditions are the main factors resulting in haze pollution in Longyou. Image 1 • Unfavourable meteorological conditions resulted in the accumulation of PM 2.5 and NO 2. • The evolution of haze pollution was mainly driven by the reactions involving NO 3 − formation. • Homogeneous reactions might play an important role nitrate formation. • Two haze episodes with the same shapes were affected by different transport paths. [ABSTRACT FROM AUTHOR]

China has implemented two national clean air actions in 2013–2017 and 2018–2020, respectively, with the aim of reducing primary emissions and hence improving air quality at a national level. It is important to examine the effectiveness of such emission reductions and assess the resulting changes in air quality. However, such evaluation is difficult as meteorological factors can amplify, or obscure the changes of air pollutants, in addition to the emission reduction. In this study, we applied the random forest machine learning technique to decouple meteorological influences from emissions changes, and examined the deweathered trends of air pollutants in 12 Chinese mega-cities during 2013–2020. The observed concentrations of all criteria pollutants except O 3 showed significant declines from 2013 to 2020, with PM 2.5 annual decline rates of 6–9% in most cities. In contrast, O 3 concentrations increased with annual growth rates of 1–9%. Compared with the observed results, all the pollutants showed smoothed but similar variation in trend and annual rate-of-change after weather normalization. The response of O 3 to NO 2 concentrations indicated significant regional differences in photochemical regimes, and the differences between observed and deweathered results provided implications for volatile organic compound emission reductions in O 3 pollution mitigation. We further evaluated the effectiveness of first and second clean air actions by removing the meteorological influence. We found that the meteorology can make negative or positive contribution in reducing pollutant concentrations from emission reduction, depending on type of pollutants, locations, and time period. Among the 12 mega-cities, only Beijing showed a positive meteorological contribution in amplifying reductions in main pollutants except O 3 during both clean air action periods. Considering the large and variable impact of meteorological effects in changing air quality, we suggest that similar deweathered analysis is needed as a routine policy evaluation tool on a regional basis. [Display omitted] • We used a random forest method to remove meteorological effect for air quality data. • The deweathered results show smoothed but similar variation in annual trends. • The meteorology can play positive or negative role depending on specific conditions. • Beijing shows positive meteorology in reducing pollutants for two clean air actions. [ABSTRACT FROM AUTHOR]