Qing Yao This email address is being protected from spambots. You need JavaScript enabled to view it.1,2, Zhiqiang Ma This email address is being protected from spambots. You need JavaScript enabled to view it.3, Jingle Liu2,4, Yulu Qiu3, Tianyi Hao1,2, Liying Yao5, Jing Ding1,2, Yingxiao Tang1,2, Ziying Cai1,2, Suqin Han1,2

1 Tianjin Environmental Meteorological Center, Tianjin 300074, China
2 CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China
3 Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
4 Tianjin Meteorological Observation Center, Tianjin 300061, China
5 Tianjin Academy of Environmental Sciences, Tianjin 300191, China


Received: May 30, 2022
Revised: August 11, 2022
Accepted: August 30, 2022

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.220226  

  • Download: PDF


Cite this article:

Yao, Q., Ma, Z., Liu, J., Qiu, Y., Hao, T., Yao, L., Ding, J., Tang, Y., Cai, Z., Han, S. (2022). Effects of Meteorological Factors on the Vertical Distribution of Peroxyacetyl Nitrate in Autumn in Tianjin. Aerosol Air Qual. Res. 22, 220226. https://doi.org/10.4209/aaqr.220226


HIGHLIGHTS

  • The boundary layer structure affects the vertical difference of PAN concentration.
  • The downdraft in the upper atmosphere leaded to the enrichment of PAN at 220 m.
  • Weak turbulence hindered the vertical exchange of PAN near the ground.
 

ABSTRACT


With the decrease of PM2.5 concentration, atmospheric photochemical pollution in North China Plain has attracted more and more attention. Peroxyacetyl nitrate (PAN) is an important product and reliable indicator of atmospheric photochemical reaction. In this study, the measured concentrations of PAN near the surface and at 220 m were obtained from the Tianjin Meteorological Tower in October 2018. The results showed that the average concentrations of PAN at ground and 220 m platform were 1.65 ± 1.34 ppb and 1.76 ± 1.41 ppb respectively during the day, and the mixture was relatively uniform. The average concentrations of PAN were 0.99 ± 0.94 ppb and 1.42 ± 1.28 ppb during the nighttime, respectively, indicating that the vertical difference was significantly increased. The standard deviation of PAN concentration was close to the average value, indicating that the concentration fluctuated greatly. The correlation coefficient between PAN and PM2.5 was higher than that of O3, indicating that stable weather was an important factor affecting PAN concentration. Based on the analysis of the vertical wind speed by the wind profile radar and ozone concentration vertical distribution data, we believe that there is a downdraft in the upper atmosphere of the boundary layer. The higher concentration of PAN at 220 m at night came from the high-altitude pollution air mass. The analysis of 40 m and 200 m turbulence data showed that the weak turbulence hindered the vertical exchange between the surface and the upper atmosphere, resulting in the high concentration of PAN unable to reach the surface. The boundary layer structure is one of the important reasons for the vertical difference of PAN concentration at night in autumn in NCP.


Keywords: Peroxyacetyl Nitrate, Vertical distribution, Ozone, PM2.5, Turbulence


1 INTRODUCTION


As typical secondary pollutants, peroxyacyl nitrates (PANs) are formed by photochemical reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the atmosphere (Aikin et al., 1982). PANs mainly include two species: peroxyacetyl nitrate (PAN) and peroxypropionyl nitrate (PPN). The former is an important characteristic pollutant of photochemical smog and was first found in photochemical smog events in Los Angeles (Stephens et al., 1956). Both O3 and PAN are important products of atmospheric photochemical reactions. Compared with PAN, which can be produced by only photochemical reactions, ground O3 is also affected by stratospheric transport; therefore, PAN is a more convincing indicator of photochemical reactions (McFadyen and Cape, 2005). Different from the low ozone concentration in winter, PAN was the most important photochemical pollution product in Beijing in winter (Zhang et al., 2014a). In polluted areas such as cities, NOx generates PAN through a series of reactions. When PAN is transported to a relatively clean area with the atmosphere, it decomposes when heated, releasing NO2. This provides an important source of nitrogen oxides in clean areas, which in turn affects the photochemical reaction process in these areas (Honrath et al., 1996; Kondo et al., 1997). The lifetime of PAN in the atmosphere is mainly affected by temperature and NO/NO2. Under the temperature conditions of the upper troposphere, the lifetime of PAN is as long as several months and can be transported globally (Kleindienst, 1994).

In recent years, the concentration of ozone in China has gradually increased, and the problem of photochemical pollution has attracted increasing attention (Zhang et al., 2011; Zhang et al., 2014a; Zhang et al., 2014b; Chan et al., 2017; Wang et al., 2010; Wang et al., 2017; Li et al., 2019). Compared with the study of ozone, observations and research of PAN in China was carried out relatively late, mainly concentrated in the large cities in the east (Zhang et al., 2014a; Gao et al., 2014; Liu et al., 2010) and the Qinghai-Tibet Plateau (Zhang et al., 2009; Xu et al., 2018). Vertical observations of PAN are helpful for understanding its source and transport characteristics. Roberts et al. (2004) investigated the vertical characteristics of PAN in spring 2002 off the west coast of North America using aircraft observation data and found that PAN showed a slight increase with altitude below 2 km. Rappengluck et al. (2004) reported that enhanced values of ozone and PAN were observed at the top of the Frohnau Tower (324 m above ground level) just north of Berlin. An observation by Baengyeong Island in South Korea (Lee et al., 2012) showed that the concentration of PAN at 1500 m was significantly higher than that on the ground, which was related to the long-distance transport from the west of the Yellow Sea. In China, there are still few vertical observations of PAN (Qiu et al., 2019; Yao et al., 2019a, 2019b).

Based on observation data of PAN near the ground and from a 220 m platform on a 250-m observation tower in Tianjin, Qiu et al. (2019) reported that the mean PAN concentrations at 220 m were 5.3–19.1% higher than ground-level values during the night, which can be attributed to differences in vertical mixing and chemical processes. On further observation, we found that the vertical difference of PAN concentration became larger, and it was often accompanied by polluted weather, in which the PM2.5 concentration exceeded the standard. It is difficult to fully explain this difference only by vertical mixing and chemical processes, and the downward transport in the boundary layer may also be an important reason for the difference. Our previous studies (Ding et al., 2018; Han et al., 2018; Zhang et al., 2020) have carried out a large number of studies on the vertical distribution of PM2.5 and ozone using the Tianjin Meteorological Tower. This provides an idea and reference for us to study the relationship between the vertical distribution of PAN and the structure of the boundary layer. The main purpose of this study was to analyze the reasons for the vertical difference in PAN concentration and to discuss the relationship between PAN, other pollutants and meteorological factors. Furthermore, we also compared the effect of the boundary layer structure on the vertical difference in PAN concentration during the pollution period and clean period. This research will improve our understanding of the temporal and spatial distributions and transport characteristics of PAN in urban areas of North China Plain (NCP) and can also provide insight for the investigation of atmospheric photochemical pollution and formulation of control strategies.

 
2 EXPERIMENTAL DESIGN


 
2.1 Sampling Site and Date

The sampling site in this study was the Tianjin Atmospheric Boundary Layer Observatory of the China Meteorological Administration (39°04′N, 117°12′E, altitude: 2.2 m, station number: 54517), located in the southern area of Tianjin city. This location is an urban area approximately 7 km away from the center of Tianjin, surrounded by residential areas to the west and south (Fig. 1). The nearest road with regular traffic is approximately 100 m away to the east. There are no direct industrial sources of atmospheric pollutants near this location. Gradient meteorological observations and atmospheric environmental observations were carried out from a 250 m high meteorological tower. The main pollutants, such as PAN, ozone, NO2 and PM2.5, were collected synchronously on the ground and 220 m platform. Measurements were taken from October 1–31, 2018, representing the typical autumn period.

Fig. 1. Sampling location.Fig. 1. Sampling location.

 
2.2 Sampling and Analysis Method

The PAN volume concentration was measured by a PANS-1000 online gas chromatograph (Focused Photonics Incorporation, Hangzhou, China). The instrument, powered by a sampling pump, used a control program to cause the gas sample to enter a column oven module, where it was separated. The separated sample was then transferred to the ECD detector, and the output electrical signals were output and recorded by the data capture program to generate the PAN detection result with a time resolution of 5 min, a detection limit of 0.02 × 10–9, and reproducibility ≤ 3%. The instrument was calibrated once before and after observations. PAN was synthesized via the 285-nm photolysis of acetone in the presence of a calibrated NO flow with a reaction yield of 93% PAN. During the observation period, the state of the instrument was stable, and all the observed data were available. Equipment calibration and data processing were carried out by Qiu et al.’s (2020) method. The NO standard gas (Linde SPECTRA Environmental Gases) was prepared at 0.97 ppm. During the measurements, the air samples at 220 meters and 3 meters above the ground were controlled by solenoid valves and then measured alternately every 15 min. Using a rotary vane vacuum pump (20 m3 h1), 220 m high air was pumped down through a Teflon pipe (32 mm inner diameter) covered by aluminum foil to block sunshine. The residence time of the air in the pipe was less than 35 s. The pressure difference between the inlet and outlet of the pipeline was less than 20 hPa. According to Qiu et al.’s (2019) method, which showed that the O3 loss was negligible, we approximately believe that the loss of PAN and other gases will also be ignored. O3 and NO2 were simultaneously measured with a UV photometric O3 analyzer (Model 49i) and a chemiluminescence NO, NO2, NOx analyzer (Model 43i). PM2.5 mass concentrations were measured using tapered element oscillating microbalances (TEOM 1405, Thermo Scientific, USA) located on the ground and on a 220 m platform. The vertical distribution of ozone concentration was observed by an atmospheric ozone lidar (Everise O3 Finder), which was based on the principle of differential absorption and uses the absorption characteristics of ozone to measure the concentration distribution of gases. The vertical detection resolution was 7.5 m, and the time resolution was 15 min. Observation data more than 300 m from the ground were selected in this study to avoid blind observation areas. The comparative observation of Qin et al. (2019) showed that the variation trend of ozone concentration retrieved at 300m byozone lidar was basically consistent with that of ground observations (Thermo 49i); therefore, the vertical distribution of high-altitude ozone concentrations can be determined by lidar.

Temperature, relative humidity, wind direction and wind speed were simultaneously measured with an automatic meteorological station (DZZ6, Zhong Huan TIG Co., Ltd.). The shortwave radiation of the sun was measured with a CNR4 net radiation sensor (Kipp & Zonen, Netherland). Sonic anemometers (CSAT, Campbell Sci., USA) were installed at 40m and 200 m on the meteorological observation tower. The sampling frequency was 10 Hz, and quality control was carried out according to Zhang et al.'s (2001) method. According to the method of Wei et al. (2018), parameters such as horizontal wind velocity, vertical wind velocity, momentum flux, turbulent kinetic energy, average kinetic energy and friction velocity were calculated. The PBL height was estimated based on ceilometer (CL31, Vaisala, Oyj, Finland) data. The maximum negative gradient from the surface in the backscatter coefficient profile was taken as the daily PBL height, and the wavelet transform method was used to detect the daily PBL height of the laser backscatter profile. The nighttime PBL height was defined as the top height of the surface stable inversion layer determined by the temperature profile observed on the 255 m tower (Han et al., 2020). Vertical velocity of the wind in the boundary layer from the wind profile radar (CFL-06) by the Tianjin Meteorological Bureau. All the data underwent data quality control and correction. The comprehensive HYSPLIT model (http://ready.arl.noaa.gov/HYSPLIT_traj.php), developed by the National Oceanic and Atmospheric Administration (NOAA) of the United States and used to provide particle trajectories, diffusion and sedimentation analysis, was adopted to analyze the back trajectory of airflow in Tianjin.

 
3 RESULTS AND DISCUSSION


 
3.1 Time Variation and Vertical Distribution of PAN

The observation period was a typical autumn on NCP. The weather was mainly sunny with little rain, which happened on October 16th (10.6 mm) and October 25th (1.4 mm). During the observation period, there were two haze weather processes occurred in mid-late October, which was weaker than usual (Cao and Gao, 2019). Fig. 2 shows the hourly distribution of the concentrations of PAN, O3, NO2 and PM2.5 in the urban area of Tianjin during the observation period. During the observation period, the average concentrations of surface PAN, O3, NO2 and PM2.5 were 1.32 ± 1.20 ppb, 19.70 ± 18.19 ppb, 24.88 ± 13.59 ppb and 44.68 ± 36.06 µg m–3, respectively. The concentrations of PAN, O3, NO2 and PM2.5 at the 220 m platform on the tower were 1.59 ± 1.36 ppb, 36.14 ± 16.66 ppb, 12.23 ± 6.57 ppb and 28.98 ± 16.16 µg m–3, respectively. The standard deviation of PAN and O3 concentration were close to the average value, indicating that the concentration fluctuated greatly, which indicated that the atmospheric diffusion conditions may affect their concentration distribution. Table 1 shows the summary of PAN concentrations in Tianjin and a comparison with other stations in the urban area. Compared with other cities in China and internationally, the concentration of PAN in autumn in Tianjin is moderate. The temporal and spatial differences in PAN concentrations in different regions were quite large; therefore it was necessary to carry out local PAN observations. The shaded areas in Fig. 2 show a typical clean period and a typical polluted period, delineated according to the PAN concentration. During most of the cleaning period (November 8–11), the PAN concentration was less than 1 ppb, while during the pollution period (November 19–22), the PAN concentration was significantly greater than 1 ppb, and the highest value was even 5 ppb. The reasons for the distribution of PAN concentration in cleaning period and pollution period will be given later in the article.

Fig. 2. Hourly variations in PAN and major atmospheric pollutants during the sampling periods.Fig. 2. Hourly variations in PAN and major atmospheric pollutants during the sampling periods.

Table 1. Summary of the PAN concentrations in Tianjin and comparison with other urban sites.

There were obvious vertical differences in the concentrations of PAN and the major air pollutants in Tianjin during the observation period. At the 220 m platform, the concentrations of O3 and PAN were 1.83 and 1.20 times those at ground level. The NO2 concentration at the 220 m platform was 49% of that at ground level, and the PM2.5 concentrations at the 60 m, 140 m and 220 m platforms were 72%, 55% and 65% of those ground level, respectively. This finding was related to the fact that NO2 and PM2.5 mainly came from the ground, while O3 and PAN come from local production and regional transport, which makes their sources more complex. The observation of Qiu et al. (2019) in September 2018 showed that the PAN concentrations at 220 m and ground level were 0.97 ppb and 0.93 ppb, respectively, and that the concentration ratio of PAN in the two layers was 1.04. The PAN observation value and concentration ratio for each layer in this study were higher than those in the study by Qiu et al. (2019), which may be related to the change in atmospheric boundary layer structure around autumn (i.e., the observation period). Compared with Qiu et al.’s (2019) results, the O3 concentration in each layer decreased significantly, and the NO2 concentration increased, which was related to the decrease in air temperature and the intensity of atmospheric photochemical reactions around late autumn during the observation period.

To further explore the vertical differences in the various pollutant concentrations, we analyzed the relationship between PAN, O3 and NO2 volume concentrations and PM2.5 mass concentrations at ground level and the 220 m platform and found the coefficient of determination (R2) and coefficient of divergence (CD) for daytime (08:00–19:00) and nighttime (20:00–07:00). The CD is defined according to Wang et al. (2005).

If the CD approaches zero, the data from ground level and the 220 m platform are considered similar; if the CD approaches one, they are considered to be very different. We regarded the ground and the 220 m platform as two sites and used a CD of 0.20 as the threshold to identify heterogeneity or homogeneity between the two sites; this approach was described in detail in Krudysz et al. (2008). As shown in Table 2, the vertical difference was small, the CD of the PAN concentration in the daytime was only 0.08, and the correlation coefficient was 0.96, indicating that PAN was evenly mixed in the daytime. The PAN concentration at 220 m at night was obviously higher than that on the ground, while the correlation coefficient decreased to 0.84 and CD increased to 0.23, indicating that the vertical difference in PAN was obvious. The vertical difference mainly occurred in the middle and last ten days of October, especially in the typical pollution period (Fig. 2). The reasons for this difference will be analyzed in detail in Section 3.3 of this article. There was a great vertical difference in the concentration of ozone or NO2 between the ground and 220 m platform at night. The concentration of ozone at the 220 m platform at night is higher than that at ground level, while the concentration of NO2 showed the opposite result. CD of the two layers of ozone at night was much higher than that in the daytime, and the NO2 had similar characteristics. The vertical distribution of PM2.5 between the ground and 220 m platform was similar during the daytime and at nighttime. The correlation of PM2.5 at ground level and the 220 m platform in the daytime was higher than that at night, but their CDs were almost equal.

Table 2. Statistical results of the observed concentrations of PAN, O3, NO2 and PM2.5 in Tianjin. The daytime and nighttime periods represent 8:00–19:00 and 20:00–07:00, respectively.


3.2 Relationship between PAN and the Main Pollutants

The correlation coefficients of PAN and O3 concentrations with the other parameters are given in Table 3. This was highlighted by the high correlation between PAN and PM2.5, which was higher in the daytime than at night and higher on the ground than at the 220 m platform. The concentration of ozone was highly related to temperature and related to the enhancement of photochemical reaction. The relationship between PAN concentration and temperature was complicated. The increase of temperature can promote the photochemical formation of PAN, while, high temperature can also promote its thermal decomposition. As shown in Fig. 3, there was a low positive correlation between PAN concentration and temperature at ground and 220 m altitude, which showed that the effect of temperature increase on the photochemical formation of PAN was greater than its thermal decomposition. Further analysis of PAN concentration difference and temperature difference at different heights showed that PAN concentration at 220 m was significantly higher than that at ground level under inversion, which indicated that PAN accumulated at high altitude and was not easy to mix in static weather, showing a strong vertical difference. The concentrations of PM2.5 and PAN were positively correlated with RH. High RH promoted the accumulation and growth of particles in the process of heavy pollution, and then increased the atmospheric extinction capacity through aerosol moisture absorption growth, thus reducing visibility and solar radiation. At the same time, the cooling of surface radiation caused significant strong temperature inversion in the surface layer, which leaded to the continuous aggravation of static and stable weather. So concentration of PM2.5 and PAN increased due to adverse meteorological conditions (Yao et al., 2019b).

Table 3. Correlations of PAN and O3 concentrations with other parameters.


Fig. 3. Differences in the concentrations of PAN and temperature between the ground and 220 m platform.Fig. 3. Differences in the concentrations of PAN and temperature between the ground and 220 m platform.

Previously, we carried out continuous observations of PAN concentrations in summer and winter from the 220 m platform of the tower (Yao et al., 2019a, 2019b). There was a high correlation between PAN and O3 during the daytime (R2 = 0.52), and R2 decreased to 0.21 at night in summer. The results of winter observation showed that there was no significant correlation between PAN and O3 (R2 = 0.10, P > 0.05), but there was a significant correlation between PAN and PM2.5 (R2 = 0.82, P < 0.01). Our observations in autumn showed that there was a significant correlation between PAN, O3 and PM2.5, which revealed that atmospheric photochemical reactions and steady weather caused by meteorological conditions were important factors affecting the PAN concentration, because the structure of the boundary layer during the observation period may be closer to that of the steady weather in winter in Tianjin. This accumulation of pollutants caused by the boundary layer structure was also reflected in the research results of Lee et al. (2013) and Liu et al. (2018).

Fig. 4 shows the observed diurnal variations in PAN, O3, NO2 and PM2.5 at ground level and the 220 m platform. The vertical difference in PAN concentration at nighttime was more obvious than that during the day, and the concentration of PAN in the two layers is almost the same. The vertical distribution of ozone was similar to that of PAN, while the opposite pattern was observed for NO2. The downward transport of O3 from the upper troposphere is an important mechanism for maintaining the high concentration of O3 at the 220 m platform at night. During the daytime, the peak value of ozone at 220 m was higher and appeared earlier than that at ground level, which may be related to the significant vertical exchange of ozone in the upper atmosphere. Neu et al. (1994) showed that the residual ozone entering the mixed layer through secondary diffusion could contribute more than 50% of the daytime maximum near-ground ozone concentration. The high concentration of ozone in the residual layer could not easily mix rapidly with the surface ozone, resulting in a great difference in the concentrations between the upper air and ground level. This difference reflected the vertical exchange characteristics of the PAN and ozone, which was related to the downward exchange of residual layer ozone caused by the change in the boundary layer structure. The characteristics of the diurnal variation in the two layers of PM2.5 were similar, showing a bimodal distribution. Compared with gaseous pollutants, PM2.5 was not fully mixed during the day because the vertical diffusivity of the particles was lower than that of gases.

Fig. 4. Differences in the diurnal concentrations of PAN and major atmospheric pollutants between the ground and 220 m platform.Fig. 4. Differences in the diurnal concentrations of PAN and major atmospheric pollutants between the ground and 220 m platform.

 
3.3 The Influence of Meteorological Conditions on the Vertical Distribution of PAN

Meteorological conditions play an important role in the PAN concentration distribution. Some studies have shown that PAN easily accumulates and forms pollution in static and stable weather (Lee et al., 2013; Liu et al., 2018). Fig. 5 shows the hourly distribution of the main meteorological factors during the observation period. The shaded areas in Fig. 5 show the clean period and polluted period, delineated according to the PAN concentration. Because the influence of meteorological factors on PAN concentration was reflected mainly in short-term changes, this study focused on performing a comparative analysis of these two typical periods. Compared with the clean period, the relative humidity during the polluted period was higher, while the wind speed, radiation intensity and mixed layer thickness were lower, which was consistent with the typical meteorological characteristics of foggy and hazy weather. As shown in Fig. 6, the PAN concentration difference between at 220 m and the ground in the pollution period was higher than that in the cleaning period. With the increase of the intensity of temperature inversion, the vertical difference of PAN increased.

Fig. 5. Hourly variations in major meteorological conditions during the sampling periods.Fig. 5. Hourly variations in major meteorological conditions during the sampling periods.

Fig. 6. Vertical differences in the PAN concentrations and temperature with clean and polluted conditions.Fig. 6. Vertical differences in the PAN concentrations and temperature with clean and polluted conditions.

Furthermore, we analyzed the difference in the PAN concentration between the ground and 220 m platform during the clean period and polluted period and provided information on wind direction and wind speed in these two typical periods. As shown in Fig. 7, the backward trajectory analysis showed that the difference in PAN concentration between the two layers was very small under long-distance northerly wind control. The concentrations of PAN were divided into four categories: 0 to < 0.5 ppb, 0.5 to < 1 ppb, 1 to < 2 ppb and > 2 ppb, representing low concentration, medium and low concentration, medium concentration and high concentration, respectively. The ground radar map showed that the surface PAN concentration was not closely related to the wind direction or wind speed, while at the 220 m platform, the low-concentration PAN (< 0.5 ppbv) was controlled by the northerly wind and a small amount of medium- and high-concentration PAN was controlled mainly by the westerly wind. The distribution characteristics of PAN during the polluted period were obviously different than the distribution characteristics at other times. With a high concentration of PAN, the backward trajectory was dominated by short-distance southerly air flow and local air flow. The radar chart showed that during the polluted period, the surface concentration was controlled mainly by a southwesterly air flow, while the concentration at the 220 m platform was controlled mainly by a westerly air flow.

Fig. 7. Vertical differences in the PAN concentrations in weather associated with clean and polluted conditions.Fig. 7. Vertical differences in the PAN concentrations in weather associated with clean and polluted conditions.

Turbulent momentum flux and heat flux are important parameters for characterizing the interaction between the earth and the atmosphere and play an important role in the transport of pollutants. The analysis of the evolution of turbulent momentum, friction velocity and heat flux during clean and polluted periods is helpful for understanding the effects of turbulent transport on steady weather and pollutant transport. Considering the high correlation between PAN and PM2.5, we used turbulence data to evaluate the vertical exchange capacity of air masses at different heights and study the vertical variation characteristics of PAN and other pollutants. Fig. 8 shows the 30 by 30 min distributions of the horizontal velocity, vertical velocity, momentum flux, turbulent kinetic energy, average kinetic energy and friction velocity at the 40 and 220 m platforms during the clean period. During the clean period, the turbulent dynamic effect was strong at 40 m and 220 m, although it was stronger at 40 m than at 220 m due to the higher surface radiation intensity at 40 m. The strong turbulence was beneficial to the full mixing of the lower atmosphere in the boundary layer. When the vertical velocity was positive, the wind was downward. The vertical wind speed was negative at 40 m in the early morning of October 9, indicating that there was a strong updraft, which led to a sudden increase in the momentum flux and friction velocity. The upward diffusion of PAN from the ground resulted in a decrease in the PAN concentration and more uniform mixing of PAN between the two layers. As a result, the vertical difference between the two layers disappeared. For comparison, Fig. 9 shows the turbulence during the polluted period, and the parameters were similar to those shown in Fig. 8. During the observation period, the horizontal wind speed and vertical wind speed at 40 m were obviously less than those at 220 m, and most of the time, the vertical wind speed at 40 m was close to zero. This result suggested that the turbulent dynamics were weak, showing significant static and stable weather characteristics, which may hinder the gas exchange between the ground and the upper air. Although the horizontal and vertical wind speeds at 220 m were relatively large, the vertical wind speed was especially large and had a positive value. This showed that there was a downward air flow and that the upper air flow could be transported downward.

Fig. 8. Temporal variations in the (a) horizontal wind velocity, (b) vertical wind velocity, (c) momentum flux, (d) turbulent kinetic energy, (e) average kinetic energy, and (f) friction velocity during the clean period (The shaded areas show nighttime).Fig. 8. Temporal variations in the (a) horizontal wind velocity, (b) vertical wind velocity, (c) momentum flux, (d) turbulent kinetic energy, (e) average kinetic energy, and (f) friction velocity during the clean period (The shaded areas show nighttime).

Fig. 9. Temporal variations in the (a) horizontal wind velocity, (b) vertical wind velocity, (c) momentum flux, (d) turbulent kinetic energy, (e) average kinetic energy, and (f) friction velocity during the polluted period (The shaded areas show nighttime).Fig. 9. Temporal variations in the (a) horizontal wind velocity, (b) vertical wind velocity, (c) momentum flux, (d) turbulent kinetic energy, (e) average kinetic energy, and (f) friction velocity during the polluted period (The shaded areas show nighttime).

Rappengluck et al. (2004) reported that long-distance transport may be the main cause of an event with an abnormally high value of ozone and PAN in Berlin. The increase in the concentrations of PAN and ozone at night was synchronous, which indicated that the effect of long-distance transport would also be very significant. Considering the long-distance transport and vertical exchange of ozone in the troposphere, the vertical distribution of ozone can be used to provide indirect evidence of the transport of PAN. Fig. 10 shows vertical velocity of the wind in the boundary layer from the wind profile radar during the polluted period. The downdraft speed reached 1–2 m s–1 on the morning of October 21. The downdraft can bring high concentrations of ozone and other gases into the ground. As shown in Fig. 11, the ozone lidar observation data showed that there was a high concentration of ozone in the air mass at heights of 900–1800 m during the study period.

Fig. 10. Vertical variations of the wind from wind profile radar observation (positive value represent descending motion).Fig. 10. Vertical variations of the wind from wind profile radar observation (positive value represent descending motion).
 

Fig. 11. Vertical distribution of ozone concentrations during the polluted period.Fig. 11. Vertical distribution of ozone concentrations during the polluted period.

We lacked vertical observation data of PAN in higher space; therefore, we could not directly show the downward transport of PAN from the upper troposphere. We believed that there was a possibility that the PAN and ozone in the upper atmosphere of the boundary layer could be transported with the downdraft, which was revealed by the turbulence observations. The small difference in the PAN concentration between the two layers during the daytime was mainly due to convection caused by strong solar radiation. This convection was suppressed at night, and the turbulence at 40 m was weak, which hindered the gas exchange between the two layers; however, the strong turbulence and downward flow at 220 m was beneficial to the continuous replenishment of PAN from the upper atmosphere of the boundary layer, resulting in a high PAN concentration at the 220 m platform. On the other hand, the surface PAN was continuously consumed due to the lack of photochemical reaction at nighttime, so there was an obvious vertical difference in the concentration of PAN between the two layers. Previous simulation results (Qiu et al., 2019) from September 2018 indicated that the high PAN concentration at 200 m was the combined result of weak vertical mixing and chemical production. In this study, the difference in the PAN concentration between the two layers at night was much greater than that in September. The calculation of PA production alone may not fully explain the high concentration of PAN in the upper layer. The unique boundary layer structure, which composed of downward transport of PAN in the upper atmosphere and weak turbulence near the surface, may also be one of the important reasons why the PAN concentration on the 220 m platform is significantly higher than that on the ground. We hope to directly obtain the direct observation data of PAN concentration in the boundary layer in the future to confirm this idea, which can provide support for clarifying the characteristics of photochemical products and formulating reasonable control strategies.

 
4 CONCLUSIONS


During the observation period, the average concentrations of surface PAN, O3, NO2 and PM2.5 were 1.32 ± 1.20 ppb, 19.70 ± 18.19 ppb, 24.88 ± 13.59 ppb and 44.68 ± 36.06 µg m–3. The concentrations of PAN, O3, NO2 and PM2.5 at the 220 m platform on the tower were 1.59 ± 1.36 ppb, 36.14 ± 16.66 ppb, 12.23 ± 6.57 ppb and 28.98 ± 16.16 µg m–3, respectively. PAN was evenly mixed at the ground level and 220 m platform during the daytime. There was a significant positive correlation between PAN, O3 and PM2.5, which showed that atmospheric photochemical reactions and stable weather caused by meteorological conditions were important factors affecting the PAN concentrations. There was a certain correlation between the PAN and O3 concentrations. The concentration of PAN was highly related to the concentration of PM2.5, which was associated with the accumulation of pollutants in haze weather.

Meteorological conditions play an important role in PAN concentration distribution. Compared with the clean period, the RH during the polluted period was higher, while the wind speed, radiation intensity and mixed layer thickness were lower, and the meteorological conditions were significantly different between the two typical periods. The backward trajectory analysis and radar maps showed that the difference in the concentrations of PAN was very small in the daytime and great at nighttime under the control of short-range southerly winds and local air flow.

During the polluted period, the vertical wind speed at 220 m positively indicated that there was strong downward air flow, while the ozone lidar observation data showed that there was a high concentration of ozone in the air mass at heights of 900–1800 m. The downdraft can bring high concentrations of ozone and other gases into the ground. The turbulence dynamics at 40 m were weak, which hindered the gas exchange between the ground and the upper air. The PAN and ozone in the upper atmosphere of the boundary layer may be transported downward, while the vertical exchange between the surface and the upper atmosphere was blocked. This was an important meteorological explanation for why the concentration of PAN was higher at 220 m than at the ground level.

 
ACKNOWLEDGMENTS


This study was supported by the National Natural Science Foundation of China (Grant No. 42130513 and 42107122).


REFERENCES


  1. Aikin, A.C., Herman, J.R., Maier, E.J., Mcquillan, C.J. (1982). Atmospheric chemistry of ethane and ethylene. J. Geophys. Res. 87, 3105–3118. https://doi.org/10.1029/JC087iC04p03105

  2. Cao, Y.N., Gao, S.Z. (2019). Analysis of the October 2018 atmospheric circulation and weather. Meteorol. Mon. 45, 135–140. https://doi.org/10.7519/j.issn.1000-0526.2021.120301 (in Chinese).

  3. Chan, K.L., Wang, S., Liu, C., Zhou, B., Wenig, M.O., Saiz-Lopez, A. (2017). On the summertime air quality and related photochemical processes in the megacity Shanghai, China. Sci. Total Environ. 580, 974–983. https://doi.org/10.1016/j.scitotenv.2016.12.052

  4. Ding, J., Zhang, Y., Han, S., Xiao, Z., Wang, J., Feng, Y. (2018). Chemical, optical andradiative characteristics of aerosols during haze episodes of winter in the North China Plain. Atmos. Environ. 181, 164–176. https://doi.org/10.1016/j.atmosenv.2018.03.006

  5. Gaffney, J.S., Marley, N.A., Cunningham, M.M., Doskey, P.V. (1999). Measurements of peroxyacyl nitrates (PANs) in Mexico City: Implications for megacity air quality impacts on regional scales. Atmos. Environ. 33, 5003–5012. https://doi.org/10.1016/S1352-2310(99)00263-0

  6. Gao, T.Y., Han, L., Wang, B., Yang, G., Xu, Z.Q., Zeng, L.M., Zhang, J.B. (2014). Peroxyacetyl nitrate observed in Beijing in August from 2005 to 2009. J. Environ. Sci. 26, 2007–2017. https://doi.org/10.1016/j.jes.2014.08.002

  7. Han, S.Q., Liu, J.L., Hao, T.Y., Zhang, Y.F., Li, P.Y., Yang, J.B., Wang, Q.L., Cai, Z.Y., Yao, Q., Zhang, M., Wang, X.J. (2018). Boundary layer structure and scavenging effect during a typical winter haze-fog episode in a core city of BTH region, China. Atmos. Environ. 179, 187–200. https://doi.org/10.1016/j.atmosenv.2018.02.023

  8. Han, S., Yao, Q., Tie, X., Zhang, Y., Zhang, M., Li, P., Cai, Z. (2020). Analysis of surface and vertical measurements of O3 and its chemical production in the NCP region, China. Atmos. Environ. 241, 117759. https://doi.org/10.1016/j.atmosenv.2020.117759

  9. Honrath, R.E., Hamlin, A.J., Merrill, J.T. (1996). Transport of ozone precursors from the Arctic troposphere to the North Atlantic region. J. Geophys. Res. 101, 29335–29351. https://doi.org/​10.1029/95jd02673

  10. Kleindienst, T.E. (1994). Recent developments in the chemistry and biology of peroxyacetyl nitrate. Res. Chem. Intermed. 20, 335–384. https://doi.org/10.1163/156856794X00379

  11. Kondo, Y., Koike, M., Kawakami, S. Singh, H.B., Nakajima, H., Gregory, L., Blake, D.R., Sachse, G.W., Merrill, J.T., Newell, R.E. (1997). Profiles and partitioning of reactive nitrogen over the Pacific Ocean in winter and early spring. J. Geophys. Res. 102, 28405–28424. https://doi.org/​10.1029/96JD03818

  12. Krudysz, M.A., Froines, J.R., Fine, P.M., Sioutas, C. (2008). Intra-community spatial variation of size-fractionated PM mass, OC, EC, and trace elements in the Long Beach, CA area. Atmos. Environ. 42, 5374–5389. https://doi.org/10.1016/j.atmosenv.2008.02.060

  13. Lee, G., Choi, H.S., Lee, T., Choi, J., Park, J.S., Ahn, J.Y. (2012). Variations of regional background peroxyacetyl nitrate in marine boundary layer over Baengyeong Island, South Korea. Atmos. Environ. 61, 533–541. https://doi.org/10.1016/j.atmosenv.2012.07.075

  14. Lee, J.B., Yoon, J.S., Jung, K., Eom, S.W., Chae, Y.Z., Cho, S.J., Kim, S.D., Sohn, J.R., Kim, K.H. (2013). Peroxyacetyl nitrate (PAN) in the urban atmosphere, Chemosphere 93, 1796–1803. https://doi.org/10.1016/j.chemosphere.2013.06.019

  15. Li, K., Jacob, D.J., Liao, H., Shen, L., Zhang, Q., Bates, K.H. (2019). Anthropogenic drivers of 2013-2017 trends in summer surface ozone in China. PNAS, 116, 422–427. https://doi.org/10.1073/​pnas.1812168116

  16. Liu, L., Wang, X.F., Chen, J.M., Xue, L.K., Wang, W.X., Wen, L., Li, D.D., Chen, T.S. (2018). Understanding unusually high levels of peroxyacetyl nitrate (PAN) in winter in Urban Jinan, China. J. Environ. Sci. 71, 249–260. https://doi.org/10.1016/j.jes.2018.05.015

  17. Liu, Z, Wang, Y.H., Gu, D.S., Zhao, C., Huey, L.G., Stickel, R., Liao, J., Shao, M., Zhu, T., Zeng, L.M., Liu, S.C., Chang, C.C., Amoroso, A., Costabile, F. (2010). Evidence of reactive aromatics as a major source of peroxyacetyl nitrate over China. Environ. Sci. Technol. 44, 7017–7022. https://doi.org/10.1021/es1007966

  18. Marley, N.A., Gaffney, J.S., Ramos-Villegas, R., Gonzalez, B.C. (2007). Comparison of measurements of peroxyacyl nitrates and primary carbonaceous aerosol concentrations in Mexico City determined in 1997 and 2003. Atmos. Chem. Phys. 7, 2277–2285. https://doi.org/10.5194/​acp-7-2277-2007

  19. McFadyen, G.G., Cape, J.N. (2005). Peroxyacetyl nitrate in eastern Scotland. Sci. Total Environ. 337, 213–222. https://doi.org/10.1016/j.scitotenv.2004.06.016

  20. Neu, U., Kunzle, T., Wanner, H. (1994). On the relation between ozone storage in the residual layer and daily variation in near-surface ozone concentration—A case study. Boundary Layer Meteorol. 69, 221–247. https://doi.org/10.1007/BF00708857

  21. Qin, L., Gao, Y.P., Wang, W.X., Zhai, H.Z., Zhang, L.N. (2019). Observation of vertical distribution of ozone based on differential absorption lidar during summer and autumn in Tianjin. Opt. Precis. Eng. 27, 1697–1703. https://doi.org/10.3788/OPE.20192708.1697 (in Chinese)

  22. Qiu, Y.L., Lin, W.L., Li, K., Chen, L., Yao, Q., Tang, Y.X., Ma, Z.Q. (2019). Vertical characteristics of peroxyacetyl nitrate (PAN) from a 250-m tower in northern China during September 2018. Atmos. Environ. 213, 55–63. https://doi.org/10.1016/j.atmosenv.2019.05.066

  23. Qiu, Y.L., Ma, Z.Q., Lin, W.L., Quan, W.J., Pu, W.W., Li, Y.R., Zhou, L.Y., Shi, Q.F. (2020). A study of peroxyacetyl nitrate at a rural site in Beijing based on continuous observations from 2015 to 2019 and the WRF-Chem model. Front. Environ. Sci. Eng. 14, 71. https://doi.org/10.1007/​s11783-020-1250-0

  24. Rappengluck, B., Forster, C., Jakobi, G., Pesch, M. (2004). Unusually high levels of PAN and ozone over Berlin, Germany, during nighttime on August 7, 1998. Atmos. Environ. 38, 6125–6134. https://doi.org/10.1016/j.atmosenv.2004.08.009

  25. Roberts, J.M., Flocke, F., Chen, G., Gouw, J., Holloway, J.S., Hübler, G., Neuman, J.A., Nicks, D.K., Nowak, J.B., Parrish, D.D., Ryerson, T.B., Sueper, D.T., Warneke, C., Fehsenfeld, F.C. (2004). Measurement of peroxycarboxylic nitric anhydrides (PANs) during the ITCT 2K2 aircraft intensive experiment. J. Geophys. Res. 109, D23S21. https://doi.org/10.1029/2004JD004960

  26. Stephens, E.R., Hanst, P.L., Doerr, R.C., Scott, W.E. (1956). Reactions of nitrogen dioxide and organic compounds in air. Ind. Eng. Chem. 48, 1498–1504. https://doi.org/10.1021/ie51400a036

  27. Sun, M., Cui, J.N., Zhao, X.M., Zhang, J.B. (2020). Impacts of precursors on peroxyacetyl nitrate (PAN) and relative formation of PAN to ozone in a southwestern megacity of China of PAN to ozone in a southwestern megacity of China. Atmos. Environ. 231, 117542. https://doi.org/​10.1016/j.atmosenv.2020.117542

  28. Wang, B., Shao, M., Roberts, J.M., Yang, G. Yang, F., Hu, M., Zeng, L.M., Zhang, Y.H., Zhang, J.B. (2010). Ground-based on-line measurements of peroxyacetyl nitrate (PAN) and peroxypropionyl nitrate (PPN) in the Pearl River Delta, China. Int. J. Environ. Anal. Chem. 90, 548–559. https://doi.org/10.1080/03067310903194972

  29. Wang, T., Xue, L., Brimblecombe, P., Lam, Y.F., Li, L., Zhang, L. (2017). Ozone pollution in China: A review of concentrations, meteorological influences, chemical precursors, and effects. Sci. Total Environ. 575, 1582–1596. https://doi.org/10.1016/j.scitotenv.2016.10.081

  30. Wang, Y., Zhuang, G., Tang, A., Yuan, H., Sun, Y., Chen, S., Zheng, A. (2005). The ion chemistry and the source of PM2.5 aerosol in Beijing. Atmos. Environ. 39, 3771–3784. https://doi.org/​10.1016/j.atmosenv.2005.03.013

  31. Wei, W., Zhang, H.S., Wu, B.G., Huang, Y.X., Cai, X.H., Song, Y., Li, J.D. (2018). Intermittent turbulence contributes to vertical dispersion of PM2.5 in the North China Plain: Cases from Tianjin. Atmos. Chem. Phys. 18, 12953–12967. https://doi.org/10.5194/acp-18-12953-2018

  32. Xu, X.B., Zhang, H.L., Lin, W.L., Wang, Y., Xu, W.J., Jia, S.H. (2018). First simultaneous measurements of peroxyacetyl nitrate (PAN) and ozone at Nam Co in the central Tibetan Plateau: Impacts from the PBL evolution and transport processes. Atmos. Chem. Phys. 18, 5199–5217. https://doi.org/10.5194/acp-18-5199-2018

  33. Yao, Q., Ma, Z.Q., Lin, W.L., Liu, J.L., Wang, X.J., Cai, Z.Y., Han, S.Q. (2019a). Transport characteristics of PAN and O3 in the lower atmosphere of the boundary layer in Tianjin in summer. Environ. Sci. 40, 67–75. https://doi.org/10.13227/j.hjkx.201805070 (in Chinese).

  34. Yao, Q., Ma, Z.Q., Liu, J.L., Wang, X.J., Yang, J.B., Cai, Z.Y., Han, S.Q. (2019b). Influence of meteorological conditions on PAN concentration in the lower boundary layer atmosphere of Tianjin in winter. China Environ. Sci. 39, 3161–3168. (in Chinese)

  35. Zhang, G., Mu, Y.J., Zhou, L.X., Zhang, C.L., Zhang, Y.Y., Liu, J.F., Fang, S.X., Yao, B. (2015). Summertime distributions of peroxyacetyl nitrate (PAN) and peroxypropionyl nitrate (PPN) in Beijing: Understanding the sources and major sink of PAN. Atmos. Environ. 103, 289–296. https://doi.org/10.1016/j.atmosenv.2014.12.035

  36. Zhang, H., Chen, J., Park, S. (2001). Turbulence structure in unstable conditions over various surfaces. Boundary Layer Meteorol. 100, 243–261. https://doi.org/10.1023/A:1019223316895

  37. Zhang, H.L., Xu, X.B., Lin, W.L., Wang, Y. (2014a). Wintertime peroxyacetyl nitrate (PAN) in the megacity Beijing: Role of photochemical and meteorological processes. J. Environ. Sci. 26, 83–96. https://doi.org/10.1016/S1001-0742(13)60384-8

  38. Zhang, J.B., Xu, Z., Yang, G., Wang, B. (2011). Peroxyacetyl nitrate (PAN) and peroxypropionyl nitrate (PPN) in urban and suburban atmospheres of Beijing, China. Atmos. Chem. Phys. Discuss. 11, 8173–8206. https://doi.org/10.5194/acpd-11-8173-2011

  39. Zhang, J.M., Wang, T., Ding, A.J., Zhou, X.H., Xue, L.K., Poon, C.N., Wu, W.S., Gao, J., Zuo, H.C., Chen, J.M., Zhang, X.C., Fan, S.J. (2009). Continuous measurement of peroxyacetyl nitrate (PAN) in suburban and remote areas of western China. Atmos. Environ. 43, 228–237. https://doi.org/10.1016/j.atmosenv.2008.09.070

  40. Zhang, Q., Yuan, B., Shao, M., Wang, X., Lu, S., Lu, K., Wang, M., Chen, L., Chang, C.C., Liu, S.C. (2014b). Variations of ground-level O3 and its precursors in Beijing in summertime between 2005 and 2011. Atmos. Chem. Phys. 14, 6089–6101.https://doi.org/10.5194/acp-14-6089-2014

  41. Zhang, T., Lin, W., Ran, L., Ma, Z., Yao, Q., Liu, J., Ming, J. (2020). Two-height distribution of ozone and nitrogen oxides during summer in urban Tianjin, China: An observational study. Aerosol Air Qual. Res. 20, 2159–2169. https://doi.org/10.4209/aaqr.2019.10.0505


Share this article with your colleagues 

 

Subscribe to our Newsletter 

Aerosol and Air Quality Research has published over 2,000 peer-reviewed articles. Enter your email address to receive latest updates and research articles to your inbox every second week.

7.3
2022CiteScore
 
 
77st percentile
Powered by
Scopus
 
   SCImago Journal & Country Rank

2022 Impact Factor: 4.0
5-Year Impact Factor: 3.4

Call for Papers for the special issue on: "Carbonaceous Aerosols in the Atmosphere"

Aerosol and Air Quality Research partners with Publons

CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit
CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit

Aerosol and Air Quality Research (AAQR) is an independently-run non-profit journal that promotes submissions of high-quality research and strives to be one of the leading aerosol and air quality open-access journals in the world. We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.