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PM2.5 is an important global air pollution issue. PM2.5 causes various problems on the environment and human health. Even though PM2.5 of the outdoor air is eliminated by particulate air filters, the chemicals adsorbed on the filtered PM2.5 can be outgassed and introduced into the semiconductor manufacturing facilities and processes, thus causing defects on the semiconductor chips by producing particles and haze as airborne molecular contamination. Therefore, estimating the amount of the outgassing from PM2.5 is a very important factor to control gaseous contaminants in the semiconductor industry. In this paper, the PM2.5 samples at different PM2.5 mass loadings were collected in Xi’an, China and evaluated using the soft X-ray radiolysis method for determining the relation between the outgassing and the PM2.5 mass loading. The PM2.5 samples were also analyzed by several methods for quantifying organic and elemental carbons, water soluble ions, and organic compounds in the PM2.5 samples. The outgassing measured by the soft X-ray method increased linearly with the PM2.5 mass loading, and the chemical analyses explained that the organic carbon (OC) was dominantly detected by the soft X-ray method in the current study. Moreover, the sampling location of the PM2.5 affected on the organic compounds of the PM2.5. [ABSTRACT FROM AUTHOR]

To investigate the chemical composition, size distribution, and mixing state of aerosol particles on heavy pollution days, single-particle aerosol mass spectrometry was conducted during 9–26 October 2015 in Xi'an, China. The measured particles were classified into six major categories: biomass burning (BB) particles, K-secondary particles, elemental carbon (EC)–related particles, metal-containing particles, dust, and organic carbon (OC) particles. BB and EC-related particles were the dominant types during the study period and mainly originated from biomass burning, vehicle emissions, and coal combustion. According to the ambient air quality index, two typical episodes were defined: clean days (CDs) and polluted days (PDs). Accumulation of BB particles and EC-related particles was the main reason for the pollution in Xi'an. Most types of particle size were larger on PDs than CDs. Each particle type was mixed with secondary species to different degrees on CDs and PDs, indicating that atmospheric aging occurred. The mixing state results demonstrated that the primary tracers were oxidized or vanished and that the amount of secondary species was increased on PDs. This study provides valuable information and a dataset to help control air pollution in the urban areas of Xi'an. Graphical abstract [ABSTRACT FROM AUTHOR]

The roles of anthropogenic emissions and weather conditions in air pollution over eastern China have been widely discussed but still controversial. Here we focus on the impact of the intraseasonal variability of midtropospheric weather circulations on air quality during 2015–2016 winter. We use the European Center for Medium‐Range Weather Forecasts reanalysis data to calculate westerly wind index (WI) and meridionality in the midtroposphere and also calculate the intensity of Siberian High at the surface. The results suggest that there were lower WI, higher meridionality, and strengthened Siberian High in January 2016 compared with the conditions in December 2015. Lower WI and higher meridionality imply for wavier midtropospheric weather circulations and stronger surface northerly winds, thereby causing more southward cold fresh air advection and resulting in the lower PM2.5 concentrations over eastern China in January 2016. Sensitivity experiments conducted by the Weather Research and Forecasting Chemical model show that the intraseasonal weather variability dominantly causes lower PM2.5 concentrations in January 2016. It not only counteracts increments in PM2.5 concentrations induced by the increased emission but also reduces PM2.5 concentrations by an extra 25–100 μg/m3. We also simulate two extreme weather patterns and compare their effects on PM2.5 concentrations. Difference in these two weather patterns induces changes in PM2.5 concentrations by 50–200 μg/m3 over eastern China and the maximal change exceeding 200 μg/m3. These findings suggest that understanding the variability of the dominant midtropospheric circulation is the key to successfully forecasting short‐term air quality over eastern China in winter. Plain Language Summary: The subseasonal variation of PM2.5 concentrations is dominantly induced by the intraseasonal variability of weather circulations during 2015–2016 winter. In the early winter (December 2015), a straight westerly wind prevails at the midtroposphere, confining cold air within the high latitudes and causing the accumulation of PM2.5 concentrations in eastern China, while in the late winter (January 2016), a north‐to‐south oriented airflow at the midtroposphere allows cold air advection to eastern China, reducing PM2.5 concentrations. Consequently, the intraseasonal weather variability leads to the maximal reduction of PM2.5 concentrations by 50–200 μg/m3. These findings suggest that understanding the variability of the midtroposphere circulation patterns is the key to successfully forecasting and improving air quality in winter. Key Points: Monthly emission change in 2015‐2016 winter results in an increment in PM2.5 concentrations by 10‐50 micrograms per cubic meter in eastern ChinaWeather variability not only offsets PM2.5 increments due to emission change but also reduces PM2.5 concentrations by an extra 25‐100 micrograms per meterMidtropospheric westerly wind circulations are the key to understanding subseasonal variations of PM2.5 concentrations [ABSTRACT FROM AUTHOR]

An intensive measurement campaign was conducted in Xi'an, China from December 2012–January 2013 to investigate the chemical composition, formation, and optical properties of PM 1. The PM 1 mass concentration (average = 138.8 ± 83.2 μg m−3) accounted for ∼50% of the PM 2.5 mass. Organic aerosols (OA) and secondary inorganic aerosols (SIA) were the most abundant PM 1 components, contributing 53.0% and 35.0% to the mass, respectively. Both primary emissions and aqueous-phase oxidation of secondary aerosols played roles in the pollution episodes. The average light scattering and absorption coefficients during the campaign were 805 ± 581 Mm−1 and 123 ± 96 Mm−1, respectively. Both the mass scattering and mass absorption efficiencies for PM 1 were higher than that for PM 2.5-1 , indicating stronger ability of light extinction for the smaller particles at visible wavelengths compared with the larger ones. The contributions of aerosol species to light extinction coefficients under two visibility conditions were estimated based on multiple linear regression models, and the OA was found to be the largest contributor to light extinction in both cases. A larger contribution of SIA to light extinction for visibility <5 km demonstrated its greater impacts on visibility during heavy pollution conditions. These findings provide insights into the importance of submicron particles for pollution and visibility degradation in northwestern China. • Organic aerosol and secondary inorganic aerosols were the most abundant PM 1 components in Xi'an during winter. • Primary emissions and aqueous-phase oxidation were essential in evolution of the pollution episodes. • Secondary inorganic aerosols (mainly NH 4 NO 3) play an important role in visibility degradation under severe air pollution. [ABSTRACT FROM AUTHOR]