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The BCT-7800A PLUS VOC online monitor system was employed to measure ambient volatile organic compounds （VOCs） in a typical solvent-using industrial park in Beijing. From January to June 2023, the pollution characteristics, source apportionment, and ozone formation potential（OFP）of VOCs were studied, and the results of a comparative analysis were also discussed between heating and non-heating periods. The results indicated that VOC concentrations from January to June 2023 were （104.21 ± 91.31） μg·m -3 on average. The concentrations of TVOCs under the influence of southerly and northerly winds were （214.18 ± 202.37） μg·m -3 and （197.56 ± 188.3） μg·m -3 , respectively. Alkanes were the species with the highest average concentration and proportion, respectively （45.53 ± 41.43） μg·m -3 . The VOC concentration during the heating period was higher than those during the non-heating period, with values of （111.57 ± 83.96） μg·m -3 and （87.92 ± 75.03） μg·m -3 , respectively. Propane and ethane were the species with the highest average concentration during the heating period. Compared with those in the non-heating period, the average concentrations of three species （propane, ethane, and n-butane） in the top ten species increased during the heating period, with average concentrations increasing by 51.94%, 54.64%, and 26.32%, respectively. The source apportionment results based on the positive matrix factorization （PMF） model indicated that the major sources of VOCs in the park during the monitoring period were printing emission sources （4.95%）, oil and gas evaporation sources （9.52%）, fuel combustion sources （15.44%）, traffic emissions sources （18.97%）, electronic equipment manufacturing （24.59%）, and industrial painting sources （26.52%）. Therefore, industrial painting sources, electronic equipment manufacturing sources, and traffic emissions sources were the emission sources that the park should focus on controlling. Compared with those during non-heating periods； industrial painting, traffic emission, and fuel combustion sources contributed more during the heating period, with VOC concentrations increasing by 15.02%, 16.53%, and 24.98%, respectively. The average OFP of VOCs from May to June during the monitoring period was 198.51 μg·m -3 and OVOCs, olefins, and aromatic hydrocarbons contributed the most to OFP, which were 47.41%, 22.15%, and 18.41%, respectively. The electronic equipment manufacturing source was the largest contributor to the summer OFP of the park and its contribution rate was 30.11%, which should be strengthened in the future.

Six sampling sites were set up in Lanzhou City, and atmospheric deposition samples were collected from April 2010 to March 2018. Subsequently, the concentration of heavy metals (Fe, Mn, Zn, Pb, Cr, Cu, Ni, and Cd) was determined to explore the temporal and spatial characteristics of heavy metals. Finally, partial correlation analysis, the enrichment factor method, and the principal component analysis method were used to identify the source of heavy metals in the atmospheric deposition. The results show that the ranking of average heavy metal content in the atmospheric deposition in Lanzhou from high to low was Fe > Mn > Zn > Pb > Cr > Cu > Ni > Cd, and Cd, Zn, and Pb were all polluted. In terms of time, except for Fe and Mn, the other elements mostly showed a trend of higher content in the heating period than that in the non-heating period, and the contents of each element in the non-heating period and the heating period in 2011 and 2013 were significantly different. In terms of sites, there were certain differences between the non-heating period and the heating period in each region; however, the differences among elements were not significant except for Zn and Cd. The source analysis results show that in the non-heating period, the heavy metals in the atmospheric deposition in Lanzhou mainly came from industrial sources, followed by traffic sources and fugitive dust sources. In the heating period, the heavy metals in the atmospheric deposition in Lanzhou mainly came from coal-burning, transportation, and industry activities, followed by secondary dust and natural sources.

To study the composition characteristics and source apportionment of PM 2.5 in the eastern part of the North China Plain, manual samples during the two-year heating period of 2016 and 2017 were collected in seven cities, including Hengshui, Cangzhou, Ji'nan, Dezhou, Binzhou, Zibo, and Liaocheng. The results showed that the average values of ρ (PM 2.5 ) during the observation periods were 137.23 μg·m -3 and 111.83 μg·m -3 , respectively, which exceeded the daily average secondary standard limit of GB 3095-2012 "Environmental Air Quality Standard" by 1.8 and 1.5 times, respectively. The mean mass of water-soluble ions accounted for 53.32% and 47.04% of ρ (PM 2.5 ), respectively, of which SNA (NO 3 - , SO 4 2- , and NH 4 + ) were the main ions. During the 2016 and 2017 observation periods, NO 3 - /SO 4 2- increased from 1.35 to 1.60, while the concentration of Cl - decreased, indicating a decrease in the impact of coal burning. The proportions of secondary organic carbon (SOC) in organic carbon (OC) were 71.63% and 55.35%, respectively, indicating the source of secondary organic carbon had decreased. Analysis of characteristic elements Fe/Al and Ba/Ni showed that dust sources and vehicle sources had increased significantly. The backward trajectories of air mass results showed that the polluted air mass mainly came from the northwest direction during the observation period. However, the PM 2.5 concentration was highest when the air mass came from the Anhui and Jiangsu provinces.

To study the atmospheric PM 2.5 pollution characteristics and sources in heating and non-heating periods in Shenyang, 113 groups of effective PM 2.5 samples were collected from January 29, 2015 to January 26, 2016, and the water-soluble ions, carbon constituents and elements in PM 2.5 were tested. The results indicated that the average PM 2.5 mass concentration in Shenyang during the sampling period was 66 μg·m -3 . Among the sampled PM 2.5 concentrations, 31.0% exceeded the daily value of the secondary standard limit of the Chinese National Ambient Air Quality Standard (75 μg·m -3 ). The average concentration and over-standard rate of PM 2.5 in the heating period (90 μg·m -3 , 68.6%) was higher than that of the non-heating period (51 μg·m -3 , 31.4%). The concentrations of the 21 elements (except Mg, Ti, Ca, Fe, and Si), water-soluble ions (except Ca 2+ ), OC, and EC were all higher in the heating period than in the non-heating period. The ratio of[NO 3 - ]showed that the influence of moving source increased obviously in the non-heating period, and fixed source was still the main contributor in the heating period. The water-soluble ions were the result of the interaction of fixed source and moving source. The NOR and SOR analyses showed that the secondary conversion of NOx was weak, and the secondary conversion of SO 4 was obvious, especially in the non-heating period. The enrichment factor showed that the elements with high EF value mainly came from coal burning, traffic pollution, and industrial emissions. The reconstructed PM 2- ]showed that the influence of moving source increased obviously in the non-heating period, and fixed source was still the main contributor in the heating period. The water-soluble ions were the result of the interaction of fixed source and moving source. The NOR and SOR analyses showed that the secondary conversion of NOx was weak, and the secondary conversion of SO 2 was obvious, especially in the non-heating period. The enrichment factor showed that the elements with high EF value mainly came from coal burning, traffic pollution, and industrial emissions. The reconstructed PM 2.5 masses were highly correlated with the measured ones. The main constituents of PM 2.5 in both heating and non-heating seasons were organic matter (28.0%, 23.1%), mineral dust (14.5%, 26.0%), and sulfate (15.1%, 19.9%), and PM 2.5 was mainly affected by the secondary particles, combustion sources and dust sources.