[Vertical Distribution Characteristics of Boundary Layer Volatile Organic Compounds in Autumn in the Mixed Industrial and Rural Areas over the Northern Suburb of Nanjing].

Based on the sounding data of VOCs in the lower troposphere (0-1000 m) in the northern suburb of Nanjing in the autumn of 2020, the vertical profile distribution, diurnal variation, and photochemical reactivity of VOCs in this area were analyzed. The results showed that the volume fraction of VOCs decreased with the increase in height (72.1×10-9±28.1×10-9-56.4×10-9±24.8×10-9). Alkanes at all heights accounted for the largest proportion (68%-75%), followed by aromatics (10%-12%), halohydrocarbons (10%-11%), alkenes (3%-7%), and acetylene (2%). The diurnal variation of the boundary layer had a great influence on the VOCs profile. The lower boundary layer in the morning and evening caused the volume fraction of VOCs to accumulate near the ground and lower in the upper layer. The vertical distribution of VOCs was more uniform in the afternoon. In the morning, the volume fraction proportion of alkenes (alkanes) with strong (weak) photochemical reactivity decreased (increased) with the increase in height, indicating that the photochemical aging of VOCs in the upper layer was significant. In the afternoon, the vertical distribution of VOCs volume fraction and OFP in the lower troposphere were more uniform. Affected by the surrounding air masses with different sources, the volume fraction and component proportion of VOCs at each height were significantly different. The alkanes in rural air masses were vertically evenly distributed, and the proportion increased gradually with the height. The vertical negative gradient of VOCs volume fraction in the urban air mass was the largest, the volume fraction of VOCs near the ground was high, and it was rich in aromatics. The proportion of aromatics increased with the increase in VOCs volume fraction between 200-400 m height of industrial air mass. The near-surface VOCs volume fraction of the highway traffic air mass was high, and alkanes accounted for the largest proportion.

Research on the Influence Mechanism of Consumers' Perceived Risk on the Advertising Avoidance Behavior of Online Targeted Advertising.

In China, online sales continue to grow against the generally adverse effects of the COVID-19 pandemic on economic development. Although advertisers favor online targeted advertising for its precision, consumers may find it intrusive and avoid it. This study constructed a conceptual model based on Stimulus-Organism-Response (SOR) theory, Approach-Avoidance Theory, and Brand Avoidance Theory to investigate the influence mechanism of consumers' perceived risk on the avoidance behavior of online targeted advertising via an online survey. Collected 436 validated data was analyzed through structural equation method in AMOS statistical software. Results showed that the positively influenced advertising avoidance, and negative emotions mediated the relationship between perceived performance risk, time-loss risk, freedom risk, and advertising avoidance, but perceived privacy risk did not influence advertising avoidance through negative emotions. Perceived COVID-19 risk moderates the effect of negative emotions on advertising avoidance. The findings provide important insights for helping governments, advertisers and online platforms into which risk perceptions influence advertising avoidance, and suggests ways to mitigate consumers risk perceptions for the mutual benefit of brands and users.

[Concentration and Reactivity of Carbonyl Compounds in the Atmosphere of North China].

To reveal the characteristics of photochemical pollution in North China, adsorbing columns with 2, 4-dinitrophenylhydrazine(DNPH) were used to sample carbonyl compounds in Shijiazhuang and Xinglong between May 2018 and April 2019. The samples were analyzed by high-performance liquid chromatography to understand the composition, volume fraction, source, ·OH loss rate, and ozone formation potential of the carbonyl compounds. A total of 13 carbonyl compounds containing carbonyl groups were determined, of which acetone, formaldehyde, and acetaldehyde were highest at(6.46±5.25)×10-9, (3.76±2.29×10-9), and(2.65±1.74)×10-9 in Shijiazhuang compared to(1.85±1.27)×10-9, (1.29±1.02)×10-9, and(0.72±0.48)×10-9 in Xinglong, respectively. The estimated maximum ozone formation potential(OFP) of formaldehyde was much higher than that of acetaldehyde; the C1/C2 and C2/C3 ozone formation potential(OFP) of formaldehyde was much higher than that of acetaldehyde; and the C1/C2 and C2/C3 values showed that vehicle exhaust and fossil fuel combustion were the main sources in Shijiazhuang in association with the higher level of industrialization. In Xinglong, the carbonyl compounds mainly originated from natural sources. Acetaldehyde(1.77 s-1), formaldehyde(1.57 s-1), and butyraldehyde(0.42 s-1) contributed most to L·OH in Shijiazhuang, and formaldehyde(0.53 s-1), acetaldehyde(0.47 s-1), and butyraldehyde(0.12 s-1) were the three main contributors to L·OH in Xinglong. The carbonyl compounds contributing most to O3 production were formaldehyde and acetaldehyde at(34.61×10-9 O3) and (16.73×10-9 O3) in Shijiazhuang, compared to (11.77×10-9 O3) and (4.47×10-9 O3) in Xinglong, respectively.

[Characteristics of Water-soluble Inorganic Ions in PM2.5 in Beijing During 2017-2018].

To explore the characteristics of water-soluble inorganic ions (WSIIs) in PM2.5 during the process of continuous improvement of air quality in Beijing in recent years, a continuous collection of PM2.5 sample campaign was conducted in Beijing from 2017 to 2018. The PM2.5 mass concentration and WSIIs were then determined. The results showed that the average concentration of PM2.5 in Beijing was (77.1±52.1) µg ·m-3, with the highest and lowest values during spring [(102.9±69.1) µg ·m-3]and summer [(54.7±19.9) µg ·m-3], respectively. The average concentration of WSIIs was (31.7±30.1) µg ·m-3, accounting for 41.1% of the PM2.5 mass, and the seasonal contributions were: autumn (45.9%) > summer (41.9%) > spring (39.9%) ≥ winter (39.2%). SNA was an important component of the WSIIs that accounted for 86.0%, 89.5%, 74.6%, and 73.0% of the total WSIIs during spring, summer, autumn, and winter, respectively. With an increase in temperature, the concentration of NO3- increased initially and then decreased, while the concentration of SO42- increased. When the relative humidity was less than 90%, the concentrations of both NO3- and SO42- increased with an increase in relative humidity. With the aggravation of pollution, the overall contribution of WSIIs in PM2.5 increased significantly, and the evolution characteristics of different ions were different. Among them, the concentration and contribution of NO3- continued to increase, while the contributions of SO42- and the ions from dust (Mg2+, Ca2+, and Na+) decreased. During the observation period, the primary sources of WSIIs were secondary conversion, combustion source, and dust. The control of coal combustion and motor vehicles is critical to reduce the emission of WSIIs. The backward trajectory analysis showed that the air masses from the south and west of Beijing corresponded to the high PM2.5 concentration and proportion of WSIIs, and the contribution of secondary ions was significant. However, the concentrations and proportions of the air masses from the northwest and north were relatively low, but the contribution of Ca2+ was high.

[Characteristics of Carbonaceous Species in PM2.5 in Southern Beijing].

To investigate the characteristics of carbonaceous species in PM2.5 in Beijing after the implementation of the Action Plan for the Prevention and Control of Air Pollution, PM2.5 was continuously sampled in the heavily polluted southern urban area of Beijing from December 2017 to December 2018. The characteristics of organic carbon (OC) and element carbon (EC) were then determined. The results showed that the annual concentrations of PM2.5, OC, and EC in Beijing varied in wide ranges of 4.2-366.3, 0.9-74.5, and 0.0-5.5 µg ·m-3, respectively, and the average mass concentration were (77.1±52.1), (11.2±7.8), and (1.2±0.8) µg ·m-3. Overall, the carbonaceous species (OC and EC) accounted for 16.1% of the PM2.5 mass. The seasonal characteristics of the OC mass concentrations were: winter [(13.8±8.7) µg ·m-3] > spring [(12.7±9.6) µg ·m-3] > autumn [(11.8±6.2) µg ·m-3] > summer [(6.5±2.1) µg ·m-3]. The concentration of the EC during the four seasons was low, ranging from 0.8 to 1.5 µg ·m-3. The annual average mass concentration and contribution of secondary organic carbon (SOC) were (5.4±5.8) µg ·m-3 and 48.2%, respectively, highlighting the significant contribution of the secondary process. With the aggravation of pollution, although the contribution proportion of OC and EC decreased, their mass concentrations during "heavily polluted" days were 6.3 and 3.2 times that of "excellent" days, respectively. Compare to non-heating period, the mass concentrations of PM2.5, OC, and SOC increased by 14.4%, 47.9%, and 72.1% in heating period, respectively, which emphasized the importance of carbonaceous species during heating periods. Potential source contribution function (PSCF) analysis showed that the southwest areas of Beijing (such as Shanxi and Henan province) were the main potential source areas of PM2.5 and OC. The high value area of the PSCF of EC was less and the main potential source area was in the south of Beijing (such as Shandong and Henan province).

[Variation Characteristics and Sources Analysis of Atmospheric Volatile Organic Compounds in Changbai Mountain Station].

Volatile organic compounds (VOCs) play very important roles in the formation of ozone and secondary organic aerosols. The concentrations, compositions, and seasonal variation of VOCs were measured in 2012 at Changbai Mountain Forest Ecosystem Research Station, a remote station in Northeast China. Weekly samples were collected in the Changbai Mountain area and analyzed via gas chromatography-mass spectrometry. The results showed that the annual mean concentration of total VOCs (TVOCs) was 10.7×10-9±6.2×10-9. Halohydrocarbon was the most abundant component, accounting for 37% of the total VOCs, followed by alkanes and aromatics, accounting for 33% and 15% respectively, and alkenes accounted for 15%. The seasonal variation of TVOCs in this area was obvious, and the order was spring >autumn >summer >winter. TVOCs concentration in spring was very significantly higher than those in any other season (P<0.05). The principal component analysis (PCA) was used to identify the sources of the VOCs. Five sources were resolved by the PCA, including traffic sources, LPG,biogenic sources, combustion sources, industrial sources and regional transportation. The HYSPLIT-4.0 model was used to analyze the effect of pollutant transport, and the results indicated that the transport of pollutants from southwest had a significant effect on the increase of VOCs concentration.

[Characteristics of Winter Atmospheric Mixing Layer Height in Beijing-Tianjin-Hebei Region and Their Relationship with the Atmospheric Pollution].

Atmospheric mixing layer height (MLH) is one of the main factors affecting the atmospheric diffusion and plays an important role in air quality assessment and distribution of the pollutants. Based on the ceilometers data, this paper has made synchronous observation on MLH in Beijing-Tianjin-Hebei region (Beijing, Tianjin, Shijiazhuang and Qinhuangdao) in heavy polluted February 2014 and analyzed the respective overall change and its regional features. Results show that in February 2014,the average of mixing layer height in Qinhuangdao is the highest, up to 865 +/- 268 m, and in Shijiazhuang is the lowest (568 +/- 207 m), Beijing's and Tianjin's are in between, 818 +/- 319 m and 834 +/- 334 m respectively; Combined with the meteorological data, we find that radiation and wind speed are main factors of the mixing layer height; The relationship between the particle concentration and mixing layer height in four sites suggests that mixing layer is less than 800 m, concentration of fine particulate matter in four sites will exceed the national standard (GB 3095-2012, 75 microg x m(-3)). During the period of observation, the proportion of days that mixing layer is less than 800 m in Beijing, Tianjin, Shijiazhuang and Qinhuangdao are 50%, 43%, 80% and 50% respectively. Shijiazhuang though nearly formation contaminant concentration is high, within the atmospheric mixed layer pollutant load is not high. Unfavorable atmospheric diffusion conditions are the main causes of heavy pollution in Shijiazhuang for a long time. The results of the study are of great significance for cognitive Beijing-Tianjin-Hebei area pollution distribution, and can provide a scientific reference for reasonable distribution of regional pollution sources.

[Effects of synoptic type on surface ozone pollution in Beijing].

Ozone (O), influenced by meteorological factors, is a primary gaseous photochemical pollutant during summer to fall in Beijing' s urban ambient. Continuous monitoring during July to September in 2008 was carried out at four sites in Beijing. Analyzed with synoptic type, the results show that the ratios of pre-low cylonic (mainly Mongolia cyclone) and pre-high anticylonic to total weather conditions are about 42% and 20%, illustrating the high-and low-ozone episodes, respectively. At the pre-low cylonic conditions, high temperature, low humidity, mountain and valley winds caused by local circulation induce average hourly maximum ozone concentration (volume fraction) up to 102.2 x 10(-9), negative correlated with atmospheric pressure with a slope of -3.4 x 10(-9) Pa(-1). The time of mountain wind changed to valley wind dominates the diurnal time of maximum ozone, generally around 14:00. At the pre-high anticylonic conditions, low temperature, high humidity and systematic north wind induce average hourly maximum ozone concentration (volume fraction) only 49.3 x 10(-9), the diurnal time of maximum ozone is deferred by continuous north wind till about 16:00. The consistency of photochemical pollution in Beijing region shows that good correlation exists between synoptic type and ozone concentration. Therefore, getting an eye on the structure and evolution of synoptic type is of great significances for forecasting the photochemical pollution.

[Application of passive sampler to monitor and study atmospheric trace gases in Beijing-Tianjin-Hebei area].

Applying of passive sampler which is a cheap and simple method, the concentrations of SO2, NO2, O3 and NH3 were monitored in ten stations as network in Beijing-Tianjin-Hebei area from Dec. 2007 to investigate the concentration level and change of contaminants as well as the compound pollution in this region. Passive sampler method was fully evaluated to check the applicability in the area and the concentration and spatial distribution of pollutants were studied in this paper. The evaluation results indicate that passive sampler method can be used for long-term sampling and the frequency was settled as one month. The coefficients of variation of parallel samplers of SO2, NO2, O3 and NH3 were 6.4%, 7.1%, 4.2% and 3.9% respectively which can represent the good stability of this method. The concentrations monitored by passive sampler had good consistency with the monthly average concentrations calculated from active monitoring. The correlation coefficients of SO2, NO2 and O3 were 0.91, 0.88 and 0.93, slopes of fitted curve were 1.25, 0.98 and 0.93 and average relative standard deviation were 23.3%, 14.9% and 8.5% respectively which indicated that passive sampler can basically meet the atmospheric sampling requirement. Short-term monitoring of NH3 also indicated that results of passive sampler and active monitoring were comparable. Passive sampler is proven to be a reliable atmospheric monitoring method and can be used in regional pollution investigation. In the summer of 2008, average concentrations which were monitored by passive sampler calculated from 10 observation stations of SO2, NO2, O3 and NH3 were (12.3 +/- 6. 3) x 10(-9), (13.2 +/- 7.0) x 10(-9), (40.5 +/- 9.5) x 10(-9) and (24.0 +/- 13.7) x 10(-9) respectively in Beijing-Tianjin-Hebei area. The concentrations of SO2 and NO2 were relatively higher in city sites and concentrations of NH3 were higher in agricultural sites. The pollution of SO2, NO, and NH3, are obviously influenced by local emission. The concentrations of O3 were about 40 x 10(-9) in most area around Beijing and Tianjin except background station Xinglong and showed regional pollution characteristic.