Abstract. Aerosol acidity plays a key role in secondary aerosol formation. The high-temporal-resolution PM2.5 pH and size-resolved aerosol pH in Beijing were calculated with ISORROPIA II. In 2016–2017, the mean PM2.5 pH (at relative humidity (RH) > 30 %) over four seasons was 4.5±0.7 (winter) > 4.4±1.2 (spring) > 4.3±0.8 (autumn) > 3.8±1.2 (summer), showing moderate acidity. In coarse-mode aerosols, Ca2+ played an important role in aerosol pH. Under heavily polluted conditions, more secondary ions accumulated in the coarse mode, leading to the acidity of the coarse-mode aerosols shifting from neutral to weakly acidic. Sensitivity tests also demonstrated the significant contribution of crustal ions to PM2.5 pH. In the North China Plain (NCP), the common driving factors affecting PM2.5 pH variation in all four seasons were SO42-, TNH3 (total ammonium (gas + aerosol)), and temperature, while unique factors were Ca2+ in spring and RH in summer. The decreasing SO42- and increasing NO3- mass fractions in PM2.5 as well as excessive NH3 in the atmosphere in the NCP in recent years are the reasons why aerosol acidity in China is lower than that in Europe and the United States. The nonlinear relationship between PM2.5 pH and TNH3 indicated that although NH3 in the NCP was abundant, the PM2.5 pH was still acidic because of the thermodynamic equilibrium between NH4+ and NH3. To reduce nitrate by controlling ammonia, the amount of ammonia must be greatly reduced below excessive quantities.

Factor analysis utilizes the covariance of compositional variables to separate sources of ambient pollutants like particulate matter (PM). However, meteorology causes concentration variations in addition to emission rate changes. Conventional positive matrix factorization (PMF) loses information from the data because of these dilution variations. By incorporating the ventilation coefficient, dispersion normalized PMF (DN-PMF) reduces the dilution effects. DN-PMF was applied to hourly speciated particulate composition data from a field campaign that included the start of the COVID-19 outbreak. DN-PMF sharpened the morning coal combustion and rush hour traffic peaks and lowered the daytime soil, aged sea salt, and waste incinerator contributions that better reflect the actual emissions. These results identified significant changes in source contributions after the COVID-19 outbreak in China. During this pandemic, secondary inorganic aerosol became the predominant PM2.5 source representing 50.5% of the mean mass. Fireworks and residential burning (32.0%), primary coal combustion emissions (13.3%), primary traffic emissions (2.1%), soil and aged sea salt (1.2%), and incinerator (0.9%) represent the other contributors. Traffic decreased dramatically (70%) compared to other sources. Soil and aged sea salt also decreased by 68%, likely from decreased traffic.

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The purpose of this study is to characterize heavy metals in ambient PM 10 (particles with aerodynamic diameter below 10 µm) and PM 2.5 (particles with aerodynamic diameter below 2.5 µm) particles in a typical integrated iron and steel industry zone (HG) and a background site (ZWY) during February 2011 to January 2012 in the Yangtze River Delta (YRD) region, China. Twelve elements were measured to study their levels, size distribution and sources. At the two sampling sites, Fe was found as the dominated metal in the total detected metals in both particle sizes, followed by Zn and Pb. They were regarded as the marker elements of iron and steel production emission along with Cr and Mn. The concentrations of all measured heavy metals in HG were 1-3.53 times higher than those measured in ZWY. When compared with previous studies, the concentrations of steel related elements (Fe, Zn, Mn) in this work were significantly high. The highest correlation coefficient was observed in HG for Fe and Zn. Additionally, Cd was found as the most enriched heavy metal by the enrichment factor analysis, followed by Zn, Pb, and Cu. The main sources contributing to heavy metals at HG site were identified by principle component analysis: steel dust (including coal combustion of coal-fired power plant, coke making and steel making emission), vehicle emission and road re-suspension dust and soil dust. Besides, steel dust was also found as the possible source of heavy metals at ZWY site. The result suggested the steel dust has influence on the whole study area.

Eight years of data on haze and visibility (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and one year of (2010) data on surface meteorological elements (relative humidity, wind speed, air temperature), visibility and the concentrations of air pollutants (PM 2.5 , SO 2 , NO 2 and O 3 ) measured each hour of each day were analyzed using correlation analysis to investigate the main factors influencing haze in Hangzhou, China. The occurrence of hazy weather has become more frequent over the past eight years in Hangzhou, and haze appears about 160 days per year. The occurrence of haze during the day was more frequent in the spring and the winter and less frequent in the summer and the autumn. Low visibility occurred in the morning, and the maximum visibility occurred in the afternoon period. The results of the statistical analysis show that the relative humidity and the concentration of PM 2.5 played the most important roles in reducing visibility. The correlation coefficients between the concentration of PM 2.5 and the concentrations of O 3 , SO 2 and NO 2 indicate that O 3 and NO 2 are the dominant factors contributing to PM 2.5 pollution, which, in turn, can lead to haze. To reduce the number of haze days, greater concern and more countermeasures should be taken to decrease the O 3 and NO 2 pollution in Hangzhou, China.

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