Abstract
Abstract Secondary inorganic aerosols (SIA, including sulfate, nitrate, and ammonium) were found to be the most dominant aerosol components during haze period. Elucidating the driving factors during liquid-phase reaction formation process of SIA is a key step for understanding the origin of airborne particulate pollution. In this work, we used online instruments and collected hourly concentrations of ions, gases, meteorological parameters in a northern city of China. Source emissions were estimated by receptor model PMF/ME2 pulling run solution (Partial Target Transformation-PMF: PTT-PMF), and six sources were identified (dust, coal combustion, vehicle exhaust, secondary sulfate, secondary nitrate and biomass burning & SOC). pH values were calculated by ISORROPIA-II, with an average value of 4.68. The relationships between RH, pH, source behaviors and concentrations of SIA during different pollution episodes were discussed. Source emissions were found to influence pH and subsequently the SIA; high RH could result in high SIA because aerosol water content in atmosphere increases with RH, which is favorable for liquid-phase reactions. Finally, we employed statistical and machine learning (Random forest classification: RFC) methods to analysis importance of driving factors on SIA formation during different pollution episodes. Results showed precursors, wet conditions, atmospheric oxidation capacity and acidity favor formation of sulfate and nitrate at different pollution levels; changes of gaseous precursors, RH and temperature are more important to determine PM2.5 pollution classification (clean, slightly polluted, moderately polluted, heavily polluted episodes). The findings of this work can provide useful information for better understanding formation mechanism of SIA, mitigating air pollution and improving human health.
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