[Analysis of the Jumping Characteristics and Influencing Factors of Ozone Pollution in Beijing].

Based on environmental monitoring data and meteorological observation data from 2016 to 2022 in Beijing, combined with backward trajectory clustering and potential source area contribution analysis, the characteristics, meteorological impacts, and potential source areas of ozone (O3) pollution were analyzed. The results showed that there was a total of 41 O3 pollution processes with jumping characteristics in Beijing from 2016 to 2022, with an average of 5.9 times a year. The occurrence time was concentrated in May to July, and the day of the jump (OJD2) was higher than the day before the jump (OJD1). The average value of ρ(O3-8h) was 78.3% higher, and the peak concentration was 78.9% higher. The high O3 concentration zone in the OJD2 region exhibited a characteristic of advancing from south to north. The main reasons for the occurrence of jumped O3 pollution in Beijing could be summarized as local accumulation caused by unfavorable meteorological conditions and regional transmission impact. The occurrence of jump-type ozone pollution was characterized by an increase in southerly wind frequency, temperature rise, pressure decrease, and precipitation decrease. The increase in southerly wind frequency provided conditions for the transport of O3 and its precursors, and rapid photochemical reactions occurred under local high temperatures, with less superimposed precipitation, comprehensively pushing up the ozone concentration level of OJD2. Six air mass transporting pathways were identified through clustering analysis; the air mass from the direction north of OJD2 decreased by 11.2%, whereas the air mass from the south and east directions increased by 6.7% and 4.4%, respectively, with the air masses mainly transmitting over short distances. The ozone concentration corresponding to the south and east directions was relatively high, making a significant contribution to Beijing's pollution. The analysis of potential source areas revealed that the main potential source areas of OJD2 ozone pollution were the central, southern, and eastern parts of Beijing-Tianjin-Hebei, which contributed 82.6% to the pollution trajectory. There was a significant contribution of regional transport during jump-type ozone pollution, and it is necessary to strengthen joint prevention and control in the Beijing-Tianjin-Hebei Region.

[Characteristics and Source Apportionment of VOCs Initial Mixing Ratio in Beijing During Summer].

To clarify the characteristics and source apportionment of the VOCs initial mixing ratio in Beijing in summer, continuous monitoring of VOCs was conducted in the Beijing urban area from May to August 2022, and the initial mixing ratio was calculated using the photochemical ratio method. The results showed that:① during the study period, initial φ(TVOCs) in the Beijing urban area were (30.0 ±11.5)×10-9, in which the proportion of VOCs and alkanes containing oxygen reached 34.2% and 33.2%, respectively. The species with high volume fractions were low carbon substances such as acetone, ethane, acetaldehyde, and propane. ② The initial TVOCs mixing ratio in Beijing showed a slightly unimodal trend, reaching the peak at 11:00 and slightly decreasing in the afternoon. ③ Isoprene, acetaldehyde, n-butanal, and ethylene were the major contributors to the generation of O3, whereas toluene, isoprene, m-paraxylene, and ethylbenzene were the major contributors to the generation of secondary organic aerosols. ④ Based on the initial mixing ratio of PMF analysis, it was found that aging background and secondary sources (30%) contributed the most to VOCs in Beijing, and motor vehicle sources (25%) were the main primary human sources. In addition, solvent and fuel volatile sources contributed 16%, combustion sources contributed 11%, industrial process sources contributed 9%, and natural sources contributed 9%. ⑤ The anthropogenic sources of Beijing were mainly from the eastern and southern regions, whereas the natural sources were from the western and northwestern regions. This research showed that vehicle emissions should be further reduced, and regional joint prevention and control to reduce VOCs in the whole region is an effective means to control VOCs in Beijing.

[Characteristics and Sources of PM2.5 and Its Light-scattering Properties with Different Chemical Compositions in Urban Area of Beijing].

In recent years, the concentration of PM2.5 in the Beijing urban area has decreased with the increase in the proportion of secondary inorganic ions. In order to explore the characteristics and sources of the light scattering of PM2.5 with different chemical compositions, PM2.5 with its chemical components and scattering coefficient were continuously measured at hourly resolution in the Beijing urban area from December 2020 to November 2021. The components, scattering characteristics, and sources of PM2.5 were analyzed. The results showed that NO3- was the major component of PM2.5 in the Beijing urban area, and the ω(NO3-) and ω(SNA) were 24% and 46% in PM2.5, respectively. PM2.5 could be divided into six types according to mass concentration and component proportion. The occurrence frequency of the good-type was the highest during the study with a similar duration in the four seasons, and the ω(SNA), ω(OM), and ω(FS) were 32%, 32%, and 28% in PM2.5, respectively. The dust(D)-type and the OM(O)-type appeared mainly in spring and summer with the lowest frequency during the study. FS and OM were their major components, and the ω(FS) and ω(OM) were 66% and 46% in PM2.5, respectively. The OM+SO42-(OS)-type, OM+NO3-(ON)-type, and NO3-(N)-type appeared mainly in the afternoon in summer, in the early morning and morning in winter, and at approximately 07:00 every day in spring. Under the condition of low humidity[relative humidity (RH)<40%], the MSE of N-type PM2.5 was the highest (4.3 m2·g-1), and that of D-type PM2.5 was the lowest (2.1 m2·g-1), reflecting the high scattering ability of SNA. The MSE increased with relative humidity. Under the condition of high humidity (RH>80%), the MSE of all types of PM2.5 rose to 1.5 to 1.8 times the values under low humidity. The variation trends of SAE showed that particle size increased with the rising of RH level. Under non-high humidity conditions, the scattering coefficients reconstructed by the revised IMPROVE formula fitted well with the measured values at hourly resolution, the correlation coefficients were between 0.81 and 0.97, and the slopes were between 1.00 and 1.21 except for that of D-type. The N-type fitting result was the best. Under high-humidity conditions, the R and the slopes were from 0.82 to 0.84 and from 0.48 to 0.53, respectively. The annual Bsca was 203.8 Mm-1, and N-type PM2.5 contributed the most, accounting for 53%, in which the large particles of NH4NO3 were the major contributor. Bsca of good-type PM2.5 was 67.2 Mm-1, in which small particles of OM were the major contributor. Bsca was 1.5 times the annual Bsca(dry), whereas the Bsca values of SNA were 1.8 to 2.1 times the Bsca(dry). The peak value of NO3- and RH simultaneously appeared around 07:00, resulting in the maximum Bsca of NH4NO3 at this time. The peak value of SO42- and the Bsca of (NH4)2SO4 mainly appeared at 16:00 and at 04:00, respectively. The diurnal variation curves of OM concentration and Bsca were consistent, and the bimodal peaks appeared at 13:00 and 20:00, respectively. In spring and winter, NO3-, SO42- and OM mainly came from the plains east of the Taihang Mountains, and their potential source regions were not in any particular place in summer and autumn; the main potential source regions of FS were the northwest areas of Beijing in spring and autumn. The flow with high RH across the south and southeast of the north China plain and the eastern rim of Bohai Sea was likely to increase the weighted potential source contribution factor values of Bsca of SNA in this region.

[Temporal Variation, Spatial Distribution, and Reactivity Characteristics of Air VOCs in Beijing 2015].

In 2015, continuous volatile organic compound (VOC) monitoring was conducted for Dongsi (urban site), the southeast boundary site Yongledian, and Dingling (background site). The average annual mole fraction of atmospheric VOCs in urban areas was(48.93±31.03)×10-9, the average annual mole fraction of the southeast boundary was (54.55±39.64)×10-9, and the average annual mole fraction for the background site was(28.25±21.26)×10-9. Considering VOC components, alkanes occupy the highest proportion, followed by oxygen-containing VOCs, olefins, aromatic hydrocarbons, halogenated hydrocarbons, and acetylene. VOC concentration was higher in winter, lower in summer, higher at night and lower in the daytime. The concentration of acetylene in urban areas was higher in spring, summer and autumn, but higher in winter at the southeast boundary site. However, in the background, a small amount of direct anthropogenic interference was detectable, with the concentration of oxygen VOCs higher at noon and in summer. The species with high mole fractions in the VOCs were identified as mainly ethane, acetylene, ethylene, acetaldehyde, propane, acetone, n-butane, dichloromethane, and other low-carbon substances. The concentrations of benzene and toluene in the high-carbon group was relatively high. From the toluene/benzene ratio, it was found that Beijing VOCs were influenced by many sources other than transportation. However, the ratio of ethane/acetylene has been found to be significantly dependent on the aging of air mass in Beijing, with the southeast boundary particularly affected by movement of the aging air mass. Changes in the ratio of isopentane/TVOC showed that high summer temperature enhanced gasoline volatilization. The southeastern boundary point of OFP was the highest, followed by the urban area, with Dingling lower. The species with greater contribution to OFP were ethylene, propylene, acetaldehyde, paraxylene and toluene, with the higher mole fraction of alkanes making little contribution to OFP.

[Variation of O3 Concentration in Different Regions of Beijing from 2006-2015].

O3 continuous monitoring data for the Dingling, Guanyuan, Liulihe, and Qianmen sites from 2006-2015 were analyzed to investigate concentration levels, variation trends, temporal variations, and relationships with precursors and meteorological factors. The results showed that the ten year average concentrations of O3 at the Dingling site were the highest at 65.2 µg·m-3, followed by concentrations at Liulihe (53.4 µg·m-3), Guanyuan (49.6 µg·m-3) and Qianmen (40.4 µg·m-3). The O3 concentrations at Dingling showed a decreasing trend[0.5 µg·(m3·a)-1], while O3 concentrations at Guanyuan[0.9 µg·(m3·a)-1], Liulihe[0.3 µg·(m3·a)-1], and Qianmen[0.3 µg·(m3·a)-1] showed an increasing trend. The highest monthly average concentrations appeared during June and August, and the highest frequency occurred in July (17 times) with average concentrations of 99.8 µg·m-3. The lowest monthly average concentrations appeared during November and February, and the highest frequency occurred in January (14 times) with an average concentration of 16.6 µg·m-3. Notably, the time for the peak concentrations of O3 appeared earlier in the day in recent years. The peak concentrations of O3 appeared at 15:00-16:00 during 2013-2015, which was 1-2 hours earlier than previous years. The heavy air pollution of O3 occurred on 11 days at the Dingling site in 2015, which was ten days more than in 2013, indicating O3 pollution in the downwind suburban regions of Beijing in summer became more and more serious. The concentrations of O3 and NO2 at Dingling showed a positive correlation, while the concentrations of O3 and NO2 at the other sites showed a negative correlation, indicating O3 formation in Dingling was sensitive to NO2 chemistry, while O3 formation at the other sites was sensitive to VOC chemistry. The concentrations of O3 showed a positive correlation with temperature and negative correlations with humidity and surface pressure. Temperature had the greatest influence on O3 concentration, followed by surface pressure and humidity. For cases when daily maximum temperature exceeded 30℃ and relative humidity was between 30% and 70%, the probability of the O3 daily maximum 8 h concentration exceeding 200 µg·m-3 was high, indicating the air quality level reached levels for light pollution and moderate pollution.